Paper Digest: Recent Papers on Text Summarization
Paper Digest Team extracted all recent Text Summarization related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Text Summarization
Paper | Author(s) | Source | Date | |
---|---|---|---|---|
1 | Large Language Models Are State-of-the-Art Evaluator for Grammatical Error Correction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate the performance of LLMs in GEC evaluation by employing prompts designed to incorporate various evaluation criteria inspired by previous research. |
Masamune Kobayashi; Masato Mita; Mamoru Komachi; | arxiv-cs.CL | 2024-03-26 |
2 | Improving Sequence-to-Sequence Models for Abstractive Text Summarization Using Meta Heuristic Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we aimed toward enhancing the present architectures and models for abstractive text summarization. |
Aditya Saxena; Ashutosh Ranjan; | arxiv-cs.CL | 2024-03-24 |
3 | Harnessing Large Language Models for Text-Rich Sequential Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Particularly, drawing inspiration from the successful application of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) models in user modeling, we introduce two unique summarization techniques in this paper, respectively hierarchical summarization and recurrent summarization. |
Zhi Zheng; Wenshuo Chao; Zhaopeng Qiu; Hengshu Zhu; Hui Xiong; | arxiv-cs.IR | 2024-03-20 |
4 | Automatic Summarization of Doctor-Patient Encounter Dialogues Using Large Language Model Through Prompt Tuning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents an approach to summarize doctor-patient dialogues using generative large language models (LLMs). |
MENGXIAN LYU et. al. | arxiv-cs.CL | 2024-03-19 |
5 | Investigating Text Shortening Strategy in BERT: Truncation Vs Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate the performance of document truncation and summarization in text classification tasks. |
Mirza Alim Mutasodirin; Radityo Eko Prasojo; | arxiv-cs.CL | 2024-03-19 |
6 | Read Between The Lines — Functionality Extraction From READMEs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We also release a human-annotated dataset called FuncRead, and develop a battery of models for the task. |
Prince Kumar; Srikanth Tamilselvam; Dinesh Garg; | arxiv-cs.CL | 2024-03-15 |
7 | TriSum: Learning Summarization Ability from Large Language Models with Structured Rationale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their large size and computational demands, coupled with privacy concerns in data transmission, limit their use in resource-constrained and privacy-centric settings. To overcome this, we introduce TriSum, a framework for distilling LLMs’ text summarization abilities into a compact, local model. |
PENGCHENG JIANG et. al. | arxiv-cs.CL | 2024-03-15 |
8 | ProSwitch: Knowledge-Guided Language Model Fine-Tuning to Generate Professional and Non-Professional Styled Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study concentrates on textual professionalism and introduces a novel methodology, named ProSwitch, which equips a language model with the ability to produce both professional and non-professional responses through knowledge-guided instruction tuning. |
Chang Zong; Yuyan Chen; Weiming Lu; Jian Shao; Yueting Zhuang; | arxiv-cs.CL | 2024-03-14 |
9 | From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While assessing response quality in terms of the whole instruction is often costly, efficiently evaluating the satisfaction rate of constraints is feasible. We investigate common constraints in NLP tasks, categorize them into three classes based on the types of their arguments, and propose a unified framework, ACT (Aligning to ConsTraints), to automatically produce supervision signals for user alignment with constraints. |
FEI WANG et. al. | arxiv-cs.CL | 2024-03-10 |
10 | ACLSum: A New Dataset for Aspect-based Summarization of Scientific Publications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, a predominant number of these resources have been (semi)-automatically generated, typically through web data crawling, resulting in subpar resources for training and evaluating summarization systems, a quality compromise that is arguably due to the substantial costs associated with generating ground-truth summaries, particularly for diverse languages and specialized domains. To address this issue, we present ACLSum, a novel summarization dataset carefully crafted and evaluated by domain experts. |
Sotaro Takeshita; Tommaso Green; Ines Reinig; Kai Eckert; Simone Paolo Ponzetto; | arxiv-cs.CL | 2024-03-08 |
11 | On The Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We study the behavior of the underlying losses between factual and non-factual examples, to understand and refine the performance of LT. We demonstrate that LT’s performance is limited when the underlying assumption that noisy targets have higher NLL loss is not satisfied, and find that word-level NLL among entities provides better signal for distinguishing factuality. |
Lorenzo Jaime Yu Flores; Arman Cohan; | arxiv-cs.CL | 2024-03-08 |
12 | Generating Insights About Financial Asks from Reddit Posts and User Interactions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes content and interaction analysis techniques for a large repository created from social media content, where people interactions are centered around financial information exchange. |
Sachin Thukral; Suyash Sangwan; Vipul Chauhan; Arnab Chatterjee; Lipika Dey; | arxiv-cs.SI | 2024-03-07 |
13 | Semi-Supervised Dialogue Abstractive Summarization Via High-Quality Pseudolabel Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel scoring approach, SiCF, which encapsulates three primary dimensions of summarization model quality: Semantic invariance (indicative of model confidence), Coverage (factual recall), and Faithfulness (factual precision). |
JIANFENG HE et. al. | arxiv-cs.CL | 2024-03-06 |
14 | German Also Hallucinates! Inconsistency Detection in News Summaries with The Absinth Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these works primarily focus on English and recent multilingual approaches lack German data. This work presents absinth, a manually annotated dataset for hallucination detection in German news summarization and explores the capabilities of novel open-source LLMs on this task in both fine-tuning and in-context learning settings. |
Laura Mascarell; Ribin Chalumattu; Annette Rios; | arxiv-cs.CL | 2024-03-06 |
15 | A Second Look on BASS — Boosting Abstractive Summarization with Unified Semantic Graphs — A Replication Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a detailed replication study of the BASS framework, an abstractive summarization system based on the notion of Unified Semantic Graphs. |
Osman Alperen Koraş; Jörg Schlötterer; Christin Seifert; | arxiv-cs.CL | 2024-03-05 |
16 | A Comprehensive Survey on Process-Oriented Automatic Text Summarization with Exploration of LLM-Based Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this survey, we aim to 1) provide a comprehensive overview of ATS from a “Process-Oriented Schema” perspective, which is best aligned with real-world implementations; 2) comprehensively review the latest LLM-based ATS works; and 3) deliver an up-to-date survey of ATS, bridging the two-year gap in the literature. |
Hanlei Jin; Yang Zhang; Dan Meng; Jun Wang; Jinghua Tan; | arxiv-cs.AI | 2024-03-05 |
17 | FENICE: Factuality Evaluation of Summarization Based on Natural Language Inference and Claim Extraction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: FENICE leverages an NLI-based alignment between information in the source document and a set of atomic facts, referred to as claims, extracted from the summary. |
Alessandro Scirè; Karim Ghonim; Roberto Navigli; | arxiv-cs.CL | 2024-03-04 |
18 | VBART: The Turkish LLM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present VBART, the first Turkish sequence-to-sequence Large Language Models (LLMs) pre-trained on a large corpus from scratch. |
Meliksah Turker; Mehmet Erdi Ari; Aydin Han; | arxiv-cs.CL | 2024-03-02 |
19 | Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we explore a general mitigation framework using Attribute Structuring (AS), which structures the summary evaluation process. |
ZELALEM GERO et. al. | arxiv-cs.CL | 2024-03-01 |
20 | EROS: Entity-Driven Controlled Policy Document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to enhance the interpretability and readability of policy documents by using controlled abstractive summarization — we enforce the generated summaries to include critical privacy-related entities (e.g., data and medium) and organization’s rationale (e.g.,target and reason) in collecting those entities. |
Joykirat Singh; Sehban Fazili; Rohan Jain; Md Shad Akhtar; | arxiv-cs.CL | 2024-02-29 |
21 | SKT5SciSumm – A Hybrid Generative Approach for Multi-Document Scientific Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given the fact that the nature of scientific text is distinctive and the input of the multi-document summarization task is substantially long, the task requires sufficient embedding generation and text truncation without losing important information. To tackle these issues, in this paper, we propose SKT5SciSumm – a hybrid framework for multi-document scientific summarization (MDSS). |
Huy Quoc To; Hung-Nghiep Tran; Andr’e Greiner-Petter; Felix Beierle; Akiko Aizawa; | arxiv-cs.CL | 2024-02-27 |
22 | BESA: Pruning Large Language Models with Blockwise Parameter-Efficient Sparsity Allocation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, their layer-wise approach results in significant perturbation to the model’s output and requires meticulous hyperparameter tuning, such as the pruning rate, which can adversely affect overall model performance. To address this, this paper introduces a novel LLM pruning technique dubbed blockwise parameter-efficient sparsity allocation (BESA) by applying a blockwise reconstruction loss. |
PENG XU et. al. | iclr | 2024-02-26 |
23 | Layer-wise Regularized Dropout for Neural Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Layer-wise Regularized Dropout (LR-Drop), which is specially designed for Transformer-based Language models. |
Shiwen Ni; Min Yang; Ruifeng Xu; Chengming Li; Xiping Hu; | arxiv-cs.CL | 2024-02-26 |
24 | Language Model Self-improvement By Reinforcement Learning Contemplation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel LMSI method, Reinforcement Learning Contemplation (RLC). |
JING-CHENG PANG et. al. | iclr | 2024-02-26 |
25 | Fusing Models with Complementary Expertise Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Training AI models that generalize across tasks and domains has long been among the open problems driving AI research. |
HONGYI WANG et. al. | iclr | 2024-02-26 |
26 | Teaching Language Models to Hallucinate Less with Synthetic Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show that reducing hallucination on a _synthetic task_ can also reduce hallucination on real-world downstream tasks. |
ERIK JONES et. al. | iclr | 2024-02-26 |
27 | Entity-level Factual Adaptiveness of Fine-tuning Based Abstractive Summarization Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we analyze the robustness of fine-tuning based summarization models to the knowledge conflict, which we call factual adaptiveness. |
JONGYOON SONG et. al. | arxiv-cs.CL | 2024-02-23 |
28 | TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new evaluation benchmark on topic-focused dialogue summarization, generated by LLMs of varying sizes. |
LIYAN TANG et. al. | arxiv-cs.CL | 2024-02-20 |
29 | Analysis of Multidomain Abstractive Summarization Using Salience Allocation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The results presented in this paper not only contribute to the evaluation of the SEASON model’s effectiveness but also illuminate the intricacies of salience allocation techniques across various types of datasets. |
Tohida Rehman; Raghubir Bose; Soumik Dey; Samiran Chattopadhyay; | arxiv-cs.CL | 2024-02-19 |
30 | Improving Factual Error Correction for Abstractive Summarization Via Data Distillation and Conditional-generation Cloze Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Improving factual consistency in abstractive summarization has been a focus of current research. One promising approach is the post-editing method. However, previous works have … |
YIYANG LI et. al. | arxiv-cs.CL | 2024-02-13 |
31 | TL;DR Progress: Multi-faceted Literature Exploration in Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents TL;DR Progress, a new tool for exploring the literature on neural text summarization. |
Shahbaz Syed; Khalid Al-Khatib; Martin Potthast; | arxiv-cs.CL | 2024-02-10 |
32 | Investigating Consistency in Query-Based Meeting Summarization: A Comparative Study of Different Embedding Methods Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With more and more advanced data analysis techniques emerging, people will expect these techniques to be applied in more complex tasks and solve problems in our daily lives. Text … |
Chen Jia-Chen; Guillem Senabre; Allane Caron; | arxiv-cs.CL | 2024-02-10 |
33 | Explaining Veracity Predictions with Evidence Summarization: A Multi-Task Model Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While significant progress has been made in this field, it has not yet reached a level of reasoning comparable to human reasoning. To address these gaps, we propose a multi-task explainable neural model for misinformation detection. |
Recep Firat Cekinel; Pinar Karagoz; | arxiv-cs.CL | 2024-02-09 |
34 | Source Identification in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we define input sentences that contain essential information in the generated summary as $\textit{source sentences}$ and study how abstractive summaries are made by analyzing the source sentences. |
Yoshi Suhara; Dimitris Alikaniotis; | arxiv-cs.CL | 2024-02-07 |
35 | A Hybrid Strategy for Chat Transcript Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is the process of condensing a piece of text to fewer sentences, while still preserving its content. Chat transcript, in this context, is a textual copy of a … |
Pratik K. Biswas; | arxiv-cs.CL | 2024-02-02 |
36 | LOCOST: State-Space Models for Long Document Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose LOCOST: an encoder-decoder architecture based on state-space models for conditional text generation with long context inputs. |
FLORIAN LE BRONNEC et. al. | arxiv-cs.CL | 2024-01-31 |
37 | GUMsley: Evaluating Entity Salience in Summarization for 12 English Genres Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present and evaluate GUMsley, the first entity salience dataset covering all named and non-named salient entities for 12 genres of English text, aligned with entity types, Wikification links and full coreference resolution annotations. |
Jessica Lin; Amir Zeldes; | arxiv-cs.CL | 2024-01-31 |
38 | Evaluating GPT-3.5’s Awareness and Summarization Abilities for European Constitutional Texts with Shared Topics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, using the renowned GPT-3.5, we leverage generative large language models to understand constitutional passages that transcend national boundaries. |
Candida M. Greco; A. Tagarelli; | arxiv-cs.CL | 2024-01-25 |
39 | Revolutionizing API Documentation Through Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study tackles the challenges associated with interpreting Application Programming Interface (API) documentation, an integral aspect of software development. |
AmirHossein Naghshzan; Sylvie Ratte; | arxiv-cs.SE | 2024-01-20 |
40 | The Radiation Oncology NLP Database Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The evaluation results in this study could serve as baseline results for future research. |
ZHENGLIANG LIU et. al. | arxiv-cs.CL | 2024-01-19 |
41 | Incremental Extractive Opinion Summarization Using Cover Trees Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the task of extractive opinion summarization in an incremental setting, where the underlying review set evolves over time. |
SOMNATH BASU ROY CHOWDHURY et. al. | arxiv-cs.CL | 2024-01-15 |
42 | Hyperparameter-Free Approach for Faster Minimum Bayes Risk Decoding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose Approximate Minimum Bayes-Risk (AMBR) decoding, a hyperparameter-free method to run MBR decoding approximately. |
Yuu Jinnai; Kaito Ariu; | arxiv-cs.AI | 2024-01-05 |
43 | Revisiting Zero-Shot Abstractive Summarization in The Era of Large Language Models from The Perspective of Position Bias Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We characterize and study zero-shot abstractive summarization in Large Language Models (LLMs) by measuring position bias, which we propose as a general formulation of the more restrictive lead bias phenomenon studied previously in the literature. |
Anshuman Chhabra; Hadi Askari; Prasant Mohapatra; | arxiv-cs.CL | 2024-01-03 |
44 | PersianLLaMA: Towards Building First Persian Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces the first large Persian language model, named PersianLLaMA, trained on a collection of Persian texts and datasets. |
Mohammad Amin Abbasi; Arash Ghafouri; Mahdi Firouzmandi; Hassan Naderi; Behrouz Minaei Bidgoli; | arxiv-cs.CL | 2023-12-25 |
45 | EntSUMv2: Dataset, Models and Evaluation for More Abstractive Entity-Centric Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents ENTSUMV2, a more abstractive version of the original entity-centric ENTSUM summarization dataset. |
Dhruv Mehra; Lingjue Xie; Ella Hofmann-Coyle; Mayank Kulkarni; Daniel Preotiuc-Pietro; | emnlp | 2023-12-22 |
46 | What to Read in A Contract? Party-Specific Summarization of Legal Obligations, Entitlements, and Prohibitions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new task of party-specific extractive summarization for legal contracts to facilitate faster reviewing and improved comprehension of rights and duties. |
Abhilasha Sancheti; Aparna Garimella; Balaji Srinivasan; Rachel Rudinger; | emnlp | 2023-12-22 |
47 | HistAlign: Improving Context Dependency in Language Generation By Aligning with History Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, we find that even with training, the performance gain stemming from the cache component of current cache-LMs is suboptimal due to the misalignment between the current hidden states and those stored in the memory. In this work, we present HistAlign, a new training approach to ensure good cache alignment such that the model receives useful signals from the history. |
David Wan; Shiyue Zhang; Mohit Bansal; | emnlp | 2023-12-22 |
48 | G-Eval: NLG Evaluation Using Gpt-4 with Better Human Alignment IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present G-Eval, a framework of using large language models with chain-of-thoughts (CoT) and a form-filling paradigm, to assess the quality of NLG outputs. |
YANG LIU et. al. | emnlp | 2023-12-22 |
49 | Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose TempoSum, a novel benchmark that contains data samples from 2010 to 2022, to understand the temporal generalization ability of abstractive summarization models. |
CHI CHEANG et. al. | emnlp | 2023-12-22 |
50 | Fidelity-Enriched Contrastive Search: Reconciling The Faithfulness-Diversity Trade-Off in Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we address the hallucination problem commonly found in natural language generation tasks. |
Wei-Lin Chen; Cheng-Kuang Wu; Hsin-Hsi Chen; Chung-Chi Chen; | emnlp | 2023-12-22 |
51 | GEMINI: Controlling The Sentence-Level Summary Style in Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: These techniques are flexible and thus difficult to be imitated by any single method. To address this issue, we propose an adaptive model, GEMINI, that integrates a rewriter and a generator to mimic the sentence rewriting and abstracting techniques, respectively. |
Guangsheng Bao; Zebin Ou; Yue Zhang; | emnlp | 2023-12-22 |
52 | Improving Summarization with Human Edits Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on a less explored form of human feedback � Human Edits. |
Zonghai Yao; Benjamin Schloss; Sai Selvaraj; | emnlp | 2023-12-22 |
53 | KCTS: Knowledge-Constrained Tree Search Decoding with Token-Level Hallucination Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unfortunately, this method incurs high training costs and may cause catastrophic forgetting for multi-tasking models. To overcome these limitations, we propose a knowledge-constrained decoding method called KCTS (Knowledge-Constrained Tree Search), which guides a frozen LM to generate text aligned with the reference knowledge at each decoding step using a knowledge classifier score and MCTS (Monte-Carlo Tree Search). |
Sehyun Choi; Tianqing Fang; Zhaowei Wang; Yangqiu Song; | emnlp | 2023-12-22 |
54 | DisCo: Distilled Student Models Co-training for Semi-supervised Text Mining Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present DisCo, a semi-supervised learning (SSL) framework for fine-tuning a cohort of small student models generated from a large PLM using knowledge distillation. |
WEIFENG JIANG et. al. | emnlp | 2023-12-22 |
55 | Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes to do zero-shot faithfulness evaluation simply with a moderately-sized foundation language model. |
Qi Jia; Siyu Ren; Yizhu Liu; Kenny Zhu; | emnlp | 2023-12-22 |
56 | Unveiling The Essence of Poetry: Introducing A Comprehensive Dataset and Benchmark for Poem Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: That being said, we propose a new task in the field of natural language understanding called �Poem Summarization�. |
RIDWAN MAHBUB et. al. | emnlp | 2023-12-22 |
57 | MRedditSum: A Multimodal Abstractive Summarization Dataset of Reddit Threads with Images Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we present mRedditSum, the first multimodal discussion summarization dataset. |
Keighley Overbay; Jaewoo Ahn; Fatemeh Pesaran zadeh; Joonsuk Park; Gunhee Kim; | emnlp | 2023-12-22 |
58 | CDD: A Large Scale Dataset for Legal Intelligence Research Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel, large-size Court Debate Dataset (CDD), which includes 30,481 court cases, totaling 1,144,425 utterances. |
Changzhen Ji; Yating Zhang; Adam Jatowt; Haipang Wu; | emnlp | 2023-12-22 |
59 | Generating Summaries with Controllable Readability Levels Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, current text generation approaches lack refined control, resulting in texts that are not customized to readers� proficiency levels. In this work, we bridge this gap and study techniques to generate summaries at specified readability levels. |
Leonardo Ribeiro; Mohit Bansal; Markus Dreyer; | emnlp | 2023-12-22 |
60 | Don’t Believe Everything You Read: Enhancing Summarization Interpretability Through Automatic Identification of Hallucinations in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper takes a deep dive into LLM behavior with respect to hallucinations, defines a token-level approach to identifying different kinds of hallucinations, and further utilizes this token-level tagging to improve the interpretability and faithfulness of LLMs in dialogue summarization tasks. Through this, the paper presents a new, enhanced dataset and a new training paradigm. |
PRIYESH VAKHARIA et. al. | arxiv-cs.CL | 2023-12-21 |
61 | APIDocBooster: An Extract-Then-Abstract Framework Leveraging Large Language Models for Augmenting API Documentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce APIDocBooster, an extract-then-abstract framework that seamlessly fuses the advantages of both extractive (i.e., enabling faithful summaries without length limitation) and abstractive summarization (i.e., producing coherent and concise summaries). |
CHENGRAN YANG et. al. | arxiv-cs.SE | 2023-12-18 |
62 | Cross-Domain Robustness of Transformer-based Keyphrase Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we explore the effectiveness of abstractive text summarization models for keyphrase selection. |
Anna Glazkova; Dmitry Morozov; | arxiv-cs.CL | 2023-12-17 |
63 | ZeroQuant(4+2): Redefining LLMs Quantization with A New FP6-Centric Strategy for Diverse Generative Tasks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study examines 4-bit quantization methods like GPTQ in large language models (LLMs), highlighting GPTQ’s overfitting and limited enhancement in Zero-Shot tasks. |
XIAOXIA WU et. al. | arxiv-cs.CL | 2023-12-13 |
64 | Unsupervised Extractive Summarization with Learnable Length Control Strategies Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces an unsupervised extractive summarization model based on a siamese network, for which we develop a trainable bidirectional prediction objective between the selected summary and the original document. |
Renlong Jie; Xiaojun Meng; Xin Jiang; Qun Liu; | arxiv-cs.AI | 2023-12-11 |
65 | Exploiting Representation Bias for Data Distillation in Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aim to discretize the vector space of the abstractive text summarization models to understand the characteristics learned between the input embedding space and the models’ encoder space. |
Yash Kumar Atri; Vikram Goyal; Tanmoy Chakraborty; | arxiv-cs.CL | 2023-12-10 |
66 | FREDSum: A Dialogue Summarization Corpus for French Political Debates Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a dataset of French political debates for the purpose of enhancing resources for multi-lingual dialogue summarization. |
Virgile Rennard; Guokan Shang; Damien Grari; Julie Hunter; Michalis Vazirgiannis; | arxiv-cs.CL | 2023-12-08 |
67 | Questioning Biases in Case Judgment Summaries: Legal Datasets or Large Language Models? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigate biases wrt Gender-related keywords, Race-related keywords, Keywords related to crime against women, Country names and religious keywords. |
Aniket Deroy; Subhankar Maity; | arxiv-cs.CL | 2023-12-01 |
68 | Evaluating Trustworthiness of AI-Enabled Decision Support Systems: Validation of The Multisource AI Scorecard Table (MAST) Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we evaluate whether MAST is associated with people’s trust perceptions in AI-enabled decision support systems (AI-DSSs). |
POURIA SALEHI et. al. | arxiv-cs.CY | 2023-11-29 |
69 | Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study introduces Ascle, a pioneering natural language processing (NLP) toolkit designed for medical text generation. |
RUI YANG et. al. | arxiv-cs.CL | 2023-11-28 |
70 | Overview of The VLSP 2022 — Abmusu Shared Task: A Data Challenge for Vietnamese Abstractive Multi-document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper reports the overview of the VLSP 2022 – Vietnamese abstractive multi-document summarization (Abmusu) shared task for Vietnamese News. |
Mai-Vu Tran; Hoang-Quynh Le; Duy-Cat Can; Quoc-An Nguyen; | arxiv-cs.CL | 2023-11-26 |
71 | Exploring Prompting Large Language Models As Explainable Metrics Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper describes the IUST NLP Lab submission to the Prompting Large Language Models as Explainable Metrics Shared Task at the Eval4NLP 2023 Workshop on Evaluation & Comparison of NLP Systems. |
Ghazaleh Mahmoudi; | arxiv-cs.CL | 2023-11-20 |
72 | LLM Aided Semi-supervision for Extractive Dialog Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a method to efficiently use unlabeled data for extractive summarization of customer-agent dialogs. |
Nishant Mishra; Gaurav Sahu; Iacer Calixto; Ameen Abu-Hanna; Issam H. Laradji; | arxiv-cs.CL | 2023-11-19 |
73 | Responsible AI Considerations in Text Summarization Research: A Review of Current Practices Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We conduct a multi-round qualitative analysis of 333 summarization papers from the ACL Anthology published between 2020-2022. |
YU LU LIU et. al. | arxiv-cs.CL | 2023-11-18 |
74 | Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we provide an extensive empirical study across five summarization datasets, two state-of-the-art pruning methods, and five instruction-tuned LLMs. |
George Chrysostomou; Zhixue Zhao; Miles Williams; Nikolaos Aletras; | arxiv-cs.CL | 2023-11-15 |
75 | AMRFact: Enhancing Summarization Factuality Evaluation with AMR-driven Training Data Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, summaries produced by these approaches are either of low coherence or lack error-type coverage. To address these issues, we propose AMRFact, a novel framework that generates factually inconsistent summaries using Abstract Meaning Representation (AMR). |
Haoyi Qiu; Kung-Hsiang Huang; Jingnong Qu; Nanyun Peng; | arxiv-cs.CL | 2023-11-15 |
76 | Enchancing Semi-Supervised Learning for Extractive Summarization with An LLM-based Pseudolabeler Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we propose a prompt-based pseudolabel selection strategy using GPT-4. |
Gaurav Sahu; Olga Vechtomova; Issam H. Laradji; | arxiv-cs.CL | 2023-11-15 |
77 | Controllable Text Summarization: Unraveling Challenges, Approaches, and Prospects — A Survey Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this survey, we formalize the Controllable Text Summarization (CTS) task, categorize controllable aspects according to their shared characteristics and objectives, and present a thorough examination of existing methods and datasets within each category. |
Ashok Urlana; Pruthwik Mishra; Tathagato Roy; Rahul Mishra; | arxiv-cs.CL | 2023-11-15 |
78 | Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we curate an evaluation-only dataset for this task setting and conduct human evaluation on 5 LLM-based summarization systems. |
YIXIN LIU et. al. | arxiv-cs.CL | 2023-11-15 |
79 | GreekT5: A Series of Greek Sequence-to-Sequence Models for News Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In any case, research in this field focuses on high resource languages such as English, while the corresponding work for low resource languages is still underdeveloped. Taking the above into account, this paper proposes a series of novel TS models for Greek news articles. |
Nikolaos Giarelis; Charalampos Mastrokostas; Nikos Karacapilidis; | arxiv-cs.CL | 2023-11-13 |
80 | Fair Abstractive Summarization of Diverse Perspectives Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we systematically investigate fair abstractive summarization for user-generated data. |
YUSEN ZHANG et. al. | arxiv-cs.CL | 2023-11-13 |
81 | Controllable Topic-Focused Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a new Transformer-based architecture capable of producing topic-focused summaries. |
Seyed Ali Bahrainian; Martin Jaggi; Carsten Eickhoff; | arxiv-cs.CL | 2023-11-11 |
82 | Legal-HNet: Mixing Legal Long-Context Tokens with Hartley Transform Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore alternatives to replace the attention-based layers with simpler token-mixing mechanisms: Hartley and Fourier transforms. |
Daniele Giofré; Sneha Ghantasala; | arxiv-cs.CL | 2023-11-08 |
83 | FloodBrain: Flood Disaster Reporting By Web-based Retrieval Augmented Generation with An LLM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, LLMs are constrained by the knowledge within their training data and are prone to generating inaccurate, or hallucinated, information. To address this, we introduce a sophisticated pipeline embodied in our tool FloodBrain (floodbrain.com), specialized in generating flood disaster impact reports by extracting and curating information from the web. |
Grace Colverd; Paul Darm; Leonard Silverberg; Noah Kasmanoff; | arxiv-cs.AI | 2023-11-05 |
84 | An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, we review the major technical innovations that underpin modern NLP models and present state-of-the-art NLP applications that employ LLMs in radiation oncology research. |
REZA KHANMOHAMMADI et. al. | arxiv-cs.CL | 2023-11-03 |
85 | Improving Factual Consistency of Text Summarization By Adversarially Decoupling Comprehension and Embellishment Abilities of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an adversarially DEcoupling method to disentangle the Comprehension and EmbellishmeNT abilities of LLMs (DECENT). |
HUAWEN FENG et. al. | arxiv-cs.CL | 2023-10-30 |
86 | Bipartite Graph Pre-training for Unsupervised Extractive Summarization with Graph Convolutional Auto-Encoders Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To do so, we propose a novel graph pre-training auto-encoder to obtain sentence embeddings by explicitly modelling intra-sentential distinctive features and inter-sentential cohesive features through sentence-word bipartite graphs. |
QIANREN MAO et. al. | arxiv-cs.CL | 2023-10-29 |
87 | Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions Using Scientific Literature Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, there is a paucity of high-quality datasets and appropriate benchmark tasks with which to evaluate these tools. We address these issues with four contributions: we release Clinfo.ai, an open-source WebApp that answers clinical questions based on dynamically retrieved scientific literature; we specify an information retrieval and abstractive summarization task to evaluate the performance of such retrieval-augmented LLM systems; we release a dataset of 200 questions and corresponding answers derived from published systematic reviews, which we name PubMed Retrieval and Synthesis (PubMedRS-200); and report benchmark results for Clinfo.ai and other publicly available OpenQA systems on PubMedRS-200. |
Alejandro Lozano; Scott L Fleming; Chia-Chun Chiang; Nigam Shah; | arxiv-cs.IR | 2023-10-24 |
88 | Correction with Backtracking Reduces Hallucination in Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a simple yet efficient technique, CoBa, to reduce hallucination in abstractive summarization. |
ZHENZHEN LIU et. al. | arxiv-cs.CL | 2023-10-24 |
89 | Rewarded Soups: Towards Pareto-optimality By Interpolating Weights Fine-tuned on Diverse Rewards Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes embracing the heterogeneity of diverse rewards by following a multi-policy strategy. |
ALEXANDRE RAME et. al. | nips | 2023-10-24 |
90 | The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce the Harvard USPTO Patent Dataset (HUPD), a large-scale, well-structured, and multi-purpose corpus of English-language patent applications filed to the United States Patent and Trademark Office (USPTO) between 2004 and 2018. |
Mirac Suzgun; Luke Melas-Kyriazi; Suproteem Sarkar; Scott D Kominers; Stuart Shieber; | nips | 2023-10-24 |
91 | Lift Yourself Up: Retrieval-augmented Text Generation with Self-Memory Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, this method is constrained by the quality of the fixed corpus from which memory is retrieved. In this paper, by exploring the duality of the primal problem: better generation also prompts better memory, we propose a novel framework, Selfmem, which addresses this limitation by iteratively employing a retrieval-augmented generator to create an unbounded memory pool and using a memory selector to choose one output as memory for the subsequent generation round. |
XIN CHENG et. al. | nips | 2023-10-24 |
92 | Leveraging Deep Learning for Abstractive Code Summarization of Unofficial Documentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an automatic approach using the BART algorithm, a state-of-the-art transformer model, to generate summaries for APIs discussed in StackOverflow. |
AmirHossein Naghshzan; Latifa Guerrouj; Olga Baysal; | arxiv-cs.SE | 2023-10-23 |
93 | PartialFormer: Modeling Part Instead of Whole Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we emphasize the importance of hidden dimension in designing lightweight FFNs, a factor often overlooked in previous architectures. |
TONG ZHENG et. al. | arxiv-cs.CL | 2023-10-23 |
94 | Controlled Randomness Improves The Performance of Transformer Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Contrasting this, in most cases, the size of the data available to solve the specific downstream task is often dwarfed by the aforementioned pre-training dataset, especially in domains where data is scarce. We introduce controlled randomness, i.e. noise, into the training process to improve fine-tuning language models and explore the performance of targeted noise in addition to the parameters of these models. |
TOBIAS DEUSSER et. al. | arxiv-cs.CL | 2023-10-20 |
95 | Enhancing Abstractiveness of Summarization Models Through Calibrated Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel approach named DisCal to enhance the level of abstractiveness (measured by n-gram overlap) without sacrificing the informativeness (measured by ROUGE) of generated summaries. |
HWANJUN SONG et. al. | arxiv-cs.CL | 2023-10-20 |
96 | Open Information Extraction: A Review of Baseline Techniques, Approaches, and Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: It briefly discusses the main approaches and the pros and cons of each method. |
Serafina Kamp; Morteza Fayazi; Zineb Benameur-El; Shuyan Yu; Ronald Dreslinski; | arxiv-cs.IR | 2023-10-17 |
97 | Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes to do zero-shot faithfulness evaluation simply with a moderately-sized foundation language model. |
Qi Jia; Siyu Ren; Yizhu Liu; Kenny Q. Zhu; | arxiv-cs.CL | 2023-10-17 |
98 | Automatic News Summerization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: After Evaluation, we integrate the best-performing models on a web application to assess their real-world capabilities and user experience. |
Kavach Dheer; Arpit Dhankhar; | arxiv-cs.CL | 2023-10-17 |
99 | Text Summarization Using Large Language Models: A Comparative Study of MPT-7b-instruct, Falcon-7b-instruct, and OpenAI Chat-GPT Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Leveraging Large Language Models (LLMs) has shown remarkable promise in enhancing summarization techniques. |
Lochan Basyal; Mihir Sanghvi; | arxiv-cs.CL | 2023-10-16 |
100 | Metric Ensembles For Hallucination Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One of the most pressing problems related to generation of abstractive summaries is the need to reduce hallucinations, information that was not included in the document being summarized, and which may be wholly incorrect. |
Grant C. Forbes; Parth Katlana; Zeydy Ortiz; | arxiv-cs.CL | 2023-10-16 |
101 | On Context Utilization in Summarization with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we conduct the first comprehensive study on context utilization and position bias in summarization. |
Mathieu Ravaut; Aixin Sun; Nancy F. Chen; Shafiq Joty; | arxiv-cs.CL | 2023-10-16 |
102 | Generating Summaries with Controllable Readability Levels Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, current text generation approaches lack refined control, resulting in texts that are not customized to readers’ proficiency levels. In this work, we bridge this gap and study techniques to generate summaries at specified readability levels. |
Leonardo F. R. Ribeiro; Mohit Bansal; Markus Dreyer; | arxiv-cs.CL | 2023-10-16 |
103 | Surveying The Landscape of Text Summarization with Deep Learning: A Comprehensive Review Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Finally, we delve into the opportunities and challenges associated with summarization tasks and their corresponding methodologies, aiming to inspire future research efforts to advance the field further. A goal of our survey is to explain how these methods differ in their requirements as understanding them is essential for choosing a technique suited for a specific setting. |
Guanghua Wang; Weili Wu; | arxiv-cs.CL | 2023-10-13 |
104 | Calibrating Likelihoods Towards Consistency in Summarization Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We argue that the main reason for such behavior is that the summarization models trained with maximum likelihood objective assign high probability to plausible sequences given the context, but they often do not accurately rank sequences by their consistency. In this work, we solve this problem by calibrating the likelihood of model generated sequences to better align with a consistency metric measured by natural language inference (NLI) models. |
POLINA ZABLOTSKAIA et. al. | arxiv-cs.CL | 2023-10-12 |
105 | Teaching Language Models to Hallucinate Less with Synthetic Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show that reducing hallucination on a synthetic task can also reduce hallucination on real-world downstream tasks. |
ERIK JONES et. al. | arxiv-cs.CL | 2023-10-10 |
106 | MemSum-DQA: Adapting An Efficient Long Document Extractive Summarizer for Document Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce MemSum-DQA, an efficient system for document question answering (DQA) that leverages MemSum, a long document extractive summarizer. |
Nianlong Gu; Yingqiang Gao; Richard H. R. Hahnloser; | arxiv-cs.CL | 2023-10-10 |
107 | Abstractive Summarization of Large Document Collections Using GPT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a method of abstractive summarization designed to scale to document collections instead of individual documents. |
Sengjie Liu; Christopher G. Healey; | arxiv-cs.AI | 2023-10-09 |
108 | Improving Summarization with Human Edits Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on a less explored form of human feedback — Human Edits. |
Zonghai Yao; Benjamin J Schloss; Sai P. Selvaraj; | arxiv-cs.CL | 2023-10-09 |
109 | Ed-cec: Improving Rare Word Recognition Using Asr Postprocessing Based on Error Detection and Context-aware Error Correction Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Automatic speech recognition (ASR) systems often encounter difficulties in accurately recognizing rare words, leading to errors that can have a negative impact on downstream tasks such as keyword spotting, intent detection, and text summarization. To address this challenge, we present a novel ASR postprocessing method that focuses on improving the recognition of rare words through error detection and context-aware error correction. |
Jiajun He; Zekun Yang; Tomoki Toda; | arxiv-cs.AI | 2023-10-08 |
110 | Automatic and Human-AI Interactive Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this tutorial, we focus on text-to-text generation, a class of natural language generation (NLG) tasks, that takes a piece of text as input and then generates a revision that is improved according to some specific criteria (e.g., readability or linguistic styles), while largely retaining the original meaning and the length of the text. |
Yao Dou; Philippe Laban; Claire Gardent; Wei Xu; | arxiv-cs.CL | 2023-10-05 |
111 | Controllable Multi-document Summarization: Coverage & Coherence Intuitive Policy with Large Language Model Based Rewards Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate for a generic controllable approach for multi-document summarization that leverages the capabilities of LLMs to refine the text. |
Litton J Kurisinkel; Nancy F chen; | arxiv-cs.CL | 2023-10-05 |
112 | Low Resource Summarization Using Pre-trained Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Considering the limited availability of resources for low-resource languages, we propose a methodology for adapting self-attentive transformer-based architecture models (mBERT, mT5) for low-resource summarization, supplemented by the construction of a new baseline dataset (76.5k article, summary pairs) in a low-resource language Urdu. |
Mubashir Munaf; Hammad Afzal; Naima Iltaf; Khawir Mahmood; | arxiv-cs.CL | 2023-10-04 |
113 | Error Norm Truncation: Robust Training in The Presence of Data Noise for Text Generation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our work, we propose Error Norm Truncation (ENT), a robust enhancement method to the standard training objective that truncates noisy data. |
Tianjian Li; Haoran Xu; Philipp Koehn; Daniel Khashabi; Kenton Murray; | arxiv-cs.CL | 2023-10-01 |
114 | Hallucination Reduction in Long Input Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we aim to reduce hallucinated outputs or hallucinations in summaries of long-form text documents. |
Tohida Rehman; Ronit Mandal; Abhishek Agarwal; Debarshi Kumar Sanyal; | arxiv-cs.CL | 2023-09-28 |
115 | BUS: Efficient and Effective Vision-Language Pre-Training with Bottom-Up Patch Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a Bottom-Up Patch Summarization approach named BUS which is inspired by the Document Summarization Task in NLP to learn a concise visual summary of lengthy visual token sequences, guided by textual semantics. |
CHAOYA JIANG et. al. | iccv | 2023-09-27 |
116 | Towards Unifying Medical Vision-and-Language Pre-Training Via Soft Prompts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The former is superior at multi-modal tasks owing to the sufficient interaction between modalities; the latter is good at uni-modal and cross-modal tasks due to the single-modality encoding ability. To take advantage of these two types, we propose an effective yet straightforward scheme named PTUnifier to unify the two types. |
Zhihong Chen; Shizhe Diao; Benyou Wang; Guanbin Li; Xiang Wan; | iccv | 2023-09-27 |
117 | BenLLMEval: A Comprehensive Evaluation Into The Potentials and Pitfalls of Large Language Models on Bengali NLP Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, this paper introduces BenLLM-Eval, which consists of a comprehensive evaluation of LLMs to benchmark their performance in the Bengali language that has modest resources. |
MOHSINUL KABIR et. al. | arxiv-cs.CL | 2023-09-22 |
118 | Summarization Is (Almost) Dead Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We develop new datasets and conduct human evaluation experiments to evaluate the zero-shot generation capability of LLMs across five distinct summarization tasks. |
Xiao Pu; Mingqi Gao; Xiaojun Wan; | arxiv-cs.CL | 2023-09-18 |
119 | Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we apply adaptation methods to eight LLMs, spanning four distinct clinical summarization tasks: radiology reports, patient questions, progress notes, and doctor-patient dialogue. |
DAVE VAN VEEN et. al. | arxiv-cs.CL | 2023-09-14 |
120 | Content Reduction, Surprisal and Information Density Estimation for Long Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an attention-based word selection method for clinical notes and study machine summarization for multiple-domain documents. |
Shaoxiong Ji; Wei Sun; Pekka Marttinen; | arxiv-cs.CL | 2023-09-12 |
121 | LiSum: Open Source Software License Summarization with Multi-Task Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we conducted a 661-participants online survey to investigate the perspectives and practices of developers towards OSS licenses. |
LINYU LI et. al. | arxiv-cs.SE | 2023-09-10 |
122 | Unsupervised Multi-document Summarization with Holistic Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new holistic framework for unsupervised multi-document extractive summarization. |
HAOPENG ZHANG et. al. | arxiv-cs.CL | 2023-09-07 |
123 | Benchmarking The Generation of Fact Checking Explanations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, instead, we address the generation of justifications (textual explanation of why a claim is classified as either true or false) and benchmark it with novel datasets and advanced baselines. |
Daniel Russo; Serra Sinem Tekiroglu; Marco Guerini; | arxiv-cs.CL | 2023-08-29 |
124 | Inducing Causal Structure for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Among such correlations, there can be spurious ones which suffer from the language prior learned from the training corpus and therefore undermine the overall effectiveness of the learned model. To tackle this issue, we introduce a Structural Causal Model (SCM) to induce the underlying causal structure of the summarization data. |
LU CHEN et. al. | arxiv-cs.CL | 2023-08-24 |
125 | Learning Summary-Worthy Visual Representation for Abstractive Summarization in Video Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel approach to learning the summary-worthy visual representation that facilitates abstractive summarization. |
ZENAN XU et. al. | ijcai | 2023-08-23 |
126 | Beyond Pure Text: Summarizing Financial Reports Based on Both Textual and Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, real-world documents, e.g., financial reports, generally contain rich data such as charts and tabular data which invalidates most existing text summarization approaches. This paper is thus motivated to propose this novel approach to simultaneously summarize both textual and tabular data. |
ZIAO WANG et. al. | ijcai | 2023-08-23 |
127 | SummHelper: Collaborative Human-Computer Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce SummHelper, a 2-phase summarization assistant designed to foster human-machine collaboration. |
Aviv Slobodkin; Niv Nachum; Shmuel Amar; Ori Shapira; Ido Dagan; | arxiv-cs.CL | 2023-08-16 |
128 | PromptSum: Parameter-Efficient Controllable Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Towards a goal of strong summarization performance under the triple conditions of parameter-efficiency, data-efficiency, and controllability, we introduce PromptSum, a method combining PT with a multi-task objective and discrete entity prompts for abstractive summarization. |
MATHIEU RAVAUT et. al. | arxiv-cs.CL | 2023-08-06 |
129 | Redundancy Aware Multi-Reference Based Gainwise Evaluation of Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unfortunately, addressing both these limitations simultaneously is not trivial. Therefore, in this paper, we propose a redundancy-aware Sem-nCG metric and demonstrate how this new metric can be used to evaluate model summaries against multiple references. |
Mousumi Akter; Shubhra Kanti Karmaker Santu; | arxiv-cs.CL | 2023-08-04 |
130 | ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce two-stage sampling and dynamic sampling approaches to improve the sampling efficiency during training sequence generation models via RL. |
CHENGLONG WANG et. al. | arxiv-cs.CL | 2023-08-04 |
131 | Fusing Multimodal Signals on Hyper-complex Space for Extreme Abstractive Text Summarization (TL;DR) of Scientific Contents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we deal with a novel task of extreme abstractive text summarization (aka TL;DR generation) by leveraging multiple input modalities. |
Yash Kumar Atri; Vikram Goyal; Tanmoy Chakraborty; | kdd | 2023-08-04 |
132 | Retrieval Augmented Generation and Representative Vector Summarization for Large Unstructured Textual Data in Medical Education Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Applications of RAG in the field of medical education are discussed in this paper. |
S. S. Manathunga; Y. A. Illangasekara; | arxiv-cs.CL | 2023-08-01 |
133 | Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Automatically summarizing radiology reports into a concise impression can reduce the manual burden of clinicians and improve the consistency of reporting. |
Jan Trienes; Paul Youssef; Jörg Schlötterer; Christin Seifert; | arxiv-cs.CL | 2023-07-24 |
134 | BUS:Efficient and Effective Vision-language Pre-training with Bottom-Up Patch Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by text summarization in natural language processing, we propose a Bottom-Up Patch Summarization approach named BUS, coordinating bottom-level extraction and top-level abstraction to learn a concise summary of lengthy visual token sequences efficiently. |
CHAOYA JIANG et. al. | arxiv-cs.CV | 2023-07-17 |
135 | Rank Your Summaries: Enhancing Bengali Text Summarization Via Ranking-based Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper aims to identify the most accurate and informative summary for a given text by utilizing a simple but effective ranking-based approach that compares the output of four different pre-trained Bengali text summarization models. |
G. M. Shahariar; Tonmoy Talukder; Rafin Alam Khan Sotez; Md. Tanvir Rouf Shawon; | arxiv-cs.CL | 2023-07-14 |
136 | Improving Factuality of Abstractive Summarization Via Contrastive Reward Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a simple but effective contrastive learning framework that incorporates recent developments in reward learning and factuality metrics. |
I-CHUN CHERN et. al. | arxiv-cs.CL | 2023-07-10 |
137 | Enhancing Biomedical Text Summarization and Question-Answering: On The Utility of Domain-Specific Pre-Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We identify a suitable model architecture and use it to show a benefit of a general-domain pre-training followed by a task-specific fine-tuning in the context of a BioASQ summarization task, leading to a novel three-step fine-tuning approach that works with only a thousand in-domain examples. |
Dima Galat; Marian-Andrei Rizoiu; | arxiv-cs.CL | 2023-07-10 |
138 | Extractive Is Not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we define a typology with five types of broad unfaithfulness problems (including and beyond not-entailment) that can appear in extractive summaries, including incorrect coreference, incomplete coreference, incorrect discourse, incomplete discourse, as well as other misleading information. |
Shiyue Zhang; David Wan; Mohit Bansal; | acl | 2023-07-08 |
139 | Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the ever-evolving nature of summarization systems, metrics, and annotated benchmarks makes factuality evaluation a moving target, and drawing clear comparisons among metrics has become increasingly difficult. In this work, we aggregate factuality error annotations from nine existing datasets and stratify them according to the underlying summarization model. |
LIYAN TANG et. al. | acl | 2023-07-08 |
140 | CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language Pairs IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a multistage data sampling algorithm to effectively train a cross-lingual summarization model capable of summarizing an article in any target language. |
ABHIK BHATTACHARJEE et. al. | acl | 2023-07-08 |
141 | Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces the �RSTformer�, a novel summarization model that comprehensively incorporates both the types and uncertainty of rhetorical relations. |
Dongqi Pu; Yifan Wang; Vera Demberg; | acl | 2023-07-08 |
142 | Balancing Lexical and Semantic Quality in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel training method in which a re-ranker balances the lexical and semantic quality. |
Jeewoo Sul; Yong Suk Choi; | acl | 2023-07-08 |
143 | Abstractive Summarizers Are Excellent Extractive Summarizers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore the potential synergies of modeling extractive summarization with an abstractive summarization system and propose three novel inference algorithms using the sequence-to-sequence architecture. |
Daniel Varab; Yumo Xu; | acl | 2023-07-08 |
144 | Unsupervised Extractive Summarization of Emotion Triggers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We instead pursue unsupervised systems that extract triggers from text. First, we introduce CovidET-EXT, augmenting (Zhan et al. , 2022)?s abstractive dataset (in the context of the COVID-19 crisis) with extractive triggers. Second, we develop new unsupervised learning models that can jointly detect emotions and summarize their triggers. |
Tiberiu Sosea; Hongli Zhan; Junyi Jessy Li; Cornelia Caragea; | acl | 2023-07-08 |
145 | Concise Answers to Complex Questions: Summarization of Long-form Answers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Together, we present the first study on summarizing long-form answers, taking a step forward for QA agents that can provide answers at multiple granularities. |
Abhilash Potluri; Fangyuan Xu; Eunsol Choi; | acl | 2023-07-08 |
146 | Summary-Oriented Vision Modeling for Multimodal Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to improve the summary quality through summary-oriented visual features. |
YUNLONG LIANG et. al. | acl | 2023-07-08 |
147 | Factually Consistent Summarization Via Reinforcement Learning with Textual Entailment Feedback IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This phenomenon is emphasized in tasks like summarization, in which the generated summaries should be corroborated by their source article. In this work we leverage recent progress on textual entailment models to directly address this problem for abstractive summarization systems. |
PAUL ROIT et. al. | acl | 2023-07-08 |
148 | Improving Factuality of Abstractive Summarization Without Sacrificing Summary Quality Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose {pasted macro �MODEL�}name (i. e. Effective Factual Summarization), a candidate summary generation and ranking technique to improve summary factuality without sacrificing quality. |
Tanay Dixit; Fei Wang; Muhao Chen; | acl | 2023-07-08 |
149 | Towards Unifying Multi-Lingual and Cross-Lingual Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aim to unify MLS and CLS into a more general setting, i. e. , many-to-many summarization (M2MS), where a single model could process documents in any language and generate their summaries also in any language. |
JIAAN WANG et. al. | acl | 2023-07-08 |
150 | NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we analyze automatic evaluation metrics for Natural Language Generation (NLG), specifically task-agnostic metrics and human-aligned metrics. |
Iftitahu Nimah; Meng Fang; Vlado Menkovski; Mykola Pechenizkiy; | acl | 2023-07-08 |
151 | Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents Z-Code++, a new pre-trained language model optimized for abstractive text summarization. |
PENGCHENG HE et. al. | acl | 2023-07-08 |
152 | Peek Across: Improving Multi-Document Modeling Via Cross-Document Question-Answering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The integration of multi-document pre-training objectives into language models has resulted in remarkable improvements in multi-document downstream tasks. In this work, we propose extending this idea by pre-training a generic multi-document model from a novel cross-document question answering pre-training objective. |
Avi Caciularu; Matthew Peters; Jacob Goldberger; Ido Dagan; Arman Cohan; | acl | 2023-07-08 |
153 | Named Entity Inclusion in Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We address the named entity omission – the drawback of many current abstractive text summarizers. |
Sergey Berezin; Tatiana Batura; | arxiv-cs.CL | 2023-07-05 |
154 | Challenges in Domain-Specific Abstractive Summarization and How to Overcome Them Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models work quite well with general-purpose data and many tasks in Natural Language Processing. |
Anum Afzal; Juraj Vladika; Daniel Braun; Florian Matthes; | arxiv-cs.CL | 2023-07-03 |
155 | Leveraging GPT-4 for Food Effect Summarization to Enhance Product-Specific Guidance Development Via Iterative Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce a simple yet effective approach, iterative prompting, which allows one to interact with ChatGPT or GPT-4 more effectively and efficiently through multi-turn interaction. |
YIWEN SHI et. al. | arxiv-cs.CL | 2023-06-28 |
156 | CoP: Factual Inconsistency Detection By Controlling The Preference Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To separate the preference for factual consistency, we propose an unsupervised framework named CoP by controlling the preference of the generation model with the help of prompt. |
Shuaijie She; Xiang Geng; Shujian Huang; Jiajun Chen; | aaai | 2023-06-26 |
157 | Preserve Context Information for Extract-Generate Long-Input Summarization Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a context-aware extract-generate framework (CAEG) for long-input text summarization. |
Ruifeng Yuan; Zili Wang; Ziqiang Cao; Wenjie Li; | aaai | 2023-06-26 |
158 | Cogito Ergo Summ: Abstractive Summarization of Biomedical Papers Via Semantic Parsing Graphs and Consistency Rewards Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents CogitoErgoSumm, the first framework for biomedical abstractive summarization equipping large pre-trained language models with rich semantic graphs. |
Giacomo Frisoni; Paolo Italiani; Stefano Salvatori; Gianluca Moro; | aaai | 2023-06-26 |
159 | Abstractive Text Summarization for Resumes With Cutting Edge NLP Transformers and LSTM Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The primary objective of this research was to classify resume text. |
Öykü Berfin Mercan; Sena Nur Cavsak; Aysu Deliahmetoglu; Senem Tanberk; | arxiv-cs.CL | 2023-06-23 |
160 | Open-Domain Text Evaluation Via Meta Distribution Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a novel approach to evaluate open-domain generation – the Meta-Distribution Methods (MDM). |
Sidi Lu; Asli Celikyilmaz; Tianlu Wang; Nanyun Peng; | arxiv-cs.CL | 2023-06-20 |
161 | QuOTeS: Query-Oriented Technical Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: When writing an academic paper, researchers often spend considerable time reviewing and summarizing papers to extract relevant citations and data to compose the Introduction and Related Work sections. To address this problem, we propose QuOTeS, an interactive system designed to retrieve sentences related to a summary of the research from a collection of potential references and hence assist in the composition of new papers. |
JUAN RAMIREZ-ORTA et. al. | arxiv-cs.IR | 2023-06-20 |
162 | One Model to Rule Them All: Ranking Slovene Summarizers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a system that recommends the most suitable summarization model for a given text. |
Aleš Žagar; Marko Robnik-Šikonja; | arxiv-cs.CL | 2023-06-20 |
163 | GUMSum: Multi-Genre Data and Evaluation for English Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Targeting ACL 2023’s ‘Reality Check’ theme, we present GUMSum, a small but carefully crafted dataset of English summaries in 12 written and spoken genres for evaluation of abstractive summarization. |
Yang Janet Liu; Amir Zeldes; | arxiv-cs.CL | 2023-06-19 |
164 | Legal Holding Extraction from Italian Case Documents Using Italian-LEGAL-BERT Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Legal holdings are used in Italy as a critical component of the legal system, serving to establish legal precedents, provide guidance for future legal decisions, and ensure … |
Daniele Licari; Praveen Bushipaka; Gabriele Marino; Giovanni Comandé; Tommaso Cucinotta; | Proceedings of the Nineteenth International Conference on … | 2023-06-19 |
165 | Using Natural Language Processing and Networks to Automate Structured Literature Reviews: An Application to Farmers Climate Change Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work aims to sensibly use Natural Language Processing by extracting variables relations and synthesizing their findings using networks while relating to key concepts dominant in relevant disciplines. |
Sofia Gil-Clavel; Tatiana Filatova; | arxiv-cs.CL | 2023-06-16 |
166 | Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the … |
SHUBO TIAN et. al. | ArXiv | 2023-06-15 |
167 | Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. |
SHUBO TIAN et. al. | arxiv-cs.CY | 2023-06-15 |
168 | ChatGPT Vs Human-authored Text: Insights Into Controllable Text Summarization and Sentence Style Transfer IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large-scale language models, like ChatGPT, have garnered significant media attention and stunned the public with their remarkable capacity for generating coherent text from short natural language prompts. In this paper, we aim to conduct a systematic inspection of ChatGPT’s performance in two controllable generation tasks, with respect to ChatGPT’s ability to adapt its output to different target audiences (expert vs. layman) and writing styles (formal vs. informal). |
Dongqi Pu; Vera Demberg; | arxiv-cs.CL | 2023-06-13 |
169 | Embodied Executable Policy Learning with Language-based Scene Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, existing LLMs with text inputs lack the capability to evolve with non-expert interactions with environments. In this work, we introduce a novel learning paradigm that generates robots’ executable actions in the form of text, derived solely from visual observations, using language-based summarization of these observations as the connecting bridge between both domains. |
Jielin Qiu; Mengdi Xu; William Han; Seungwhan Moon; Ding Zhao; | arxiv-cs.RO | 2023-06-09 |
170 | Echoes from Alexandria: A Large Resource for Multilingual Book Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The task of full-book summarization presents additional challenges which are hard to tackle with current resources, due to their limited size and availability in English only. To overcome these limitations, we present Echoes from Alexandria, or in shortened form, Echoes, a large resource for multilingual book summarization. |
Alessandro Scirè; Simone Conia; Simone Ciciliano; Roberto Navigli; | arxiv-cs.CL | 2023-06-07 |
171 | Absformer: Transformer-based Model for Unsupervised Multi-Document Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we consider the unsupervised abstractive MDS setting where there are only documents with no groundtruh summaries provided, and we propose Absformer, a new Transformer-based method for unsupervised abstractive summary generation. |
Mohamed Trabelsi; Huseyin Uzunalioglu; | arxiv-cs.CL | 2023-06-07 |
172 | MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: (3) Benchmark tests performed on the proposed dataset to assess various tasks and methods, including \textit{video summarization}, \textit{text summarization}, and \textit{multimodal summarization}. |
JIELIN QIU et. al. | arxiv-cs.CV | 2023-06-07 |
173 | Rewarded Soups: Towards Pareto-optimal Alignment By Interpolating Weights Fine-tuned on Diverse Rewards IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes embracing the heterogeneity of diverse rewards by following a multi-policy strategy. |
ALEXANDRE RAMÉ et. al. | arxiv-cs.LG | 2023-06-07 |
174 | Correction of Errors in Preference Ratings from Automated Metrics for Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a statistical model of Text Generation evaluation that accounts for the error-proneness of automated metrics when used to generate preference rankings between system outputs. |
Jan Deriu; Pius von Däniken; Don Tuggener; Mark Cieliebak; | arxiv-cs.CL | 2023-06-06 |
175 | Interactive Editing for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Although recent advancements in neural summarization models can assist in crafting general-purpose summaries, human writers often have specific requirements that call for a more customized approach. To address this need, we introduce REVISE (Refinement and Editing via Iterative Summarization Enhancement), an innovative framework designed to facilitate iterative editing and refinement of draft summaries by human writers. |
Yujia Xie; Xun Wang; Si-Qing Chen; Wayne Xiong; Pengcheng He; | arxiv-cs.CL | 2023-06-05 |
176 | Efficient GPT Model Pre-training Using Tensor Train Matrix Representation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large-scale transformer models have shown remarkable performance in language modelling tasks. |
Viktoriia Chekalina; Georgii Novikov; Julia Gusak; Ivan Oseledets; Alexander Panchenko; | arxiv-cs.AI | 2023-06-05 |
177 | How Ready Are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Automatic summarization of legal case judgements has traditionally been attempted by using extractive summarization methods. |
Aniket Deroy; Kripabandhu Ghosh; Saptarshi Ghosh; | arxiv-cs.CL | 2023-06-01 |
178 | Hybrid Long Document Summarization Using C2F-FAR and ChatGPT: A Practical Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we use ChatGPT, the latest breakthrough in the field of large language models (LLMs), together with the extractive summarization model C2F-FAR (Coarse-to-Fine Facet-Aware Ranking) to propose a hybrid extraction and summarization pipeline for long documents such as business articles and books. |
Guang Lu; Sylvia B. Larcher; Tu Tran; | arxiv-cs.CL | 2023-06-01 |
179 | Multi-Dimensional Evaluation of Text Summarization with In-Context Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we study the efficacy of large language models as multi-dimensional evaluators using in-context learning, obviating the need for large training datasets. |
SAMEER JAIN et. al. | arxiv-cs.CL | 2023-06-01 |
180 | Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Reranking Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a simple approach for the abstractive summarization of long legal opinions that considers the argument structure of the document. |
Mohamed Elaraby; Yang Zhong; Diane Litman; | arxiv-cs.CL | 2023-06-01 |
181 | Dehallucinating Large Language Models Using Formal Methods Guided Iterative Prompting IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large language models (LLMs) such as ChatGPT have been trained to generate human-like responses to natural language prompts. LLMs use a vast corpus of text data for training, and … |
SUSMIT JHA et. al. | 2023 IEEE International Conference on Assured Autonomy … | 2023-06-01 |
182 | Factually Consistent Summarization Via Reinforcement Learning with Textual Entailment Feedback IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This phenomenon is emphasized in tasks like summarization, in which the generated summaries should be corroborated by their source article. In this work, we leverage recent progress on textual entailment models to directly address this problem for abstractive summarization systems. |
PAUL ROIT et. al. | arxiv-cs.CL | 2023-05-31 |
183 | IDAS: Intent Discovery with Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We contribute the IDAS approach, which collects a set of descriptive utterance labels by prompting a Large Language Model, starting from a well-chosen seed set of prototypical utterances, to bootstrap an In-Context Learning procedure to generate labels for non-prototypical utterances. |
Maarten De Raedt; Fréderic Godin; Thomas Demeester; Chris Develder; | arxiv-cs.CL | 2023-05-31 |
184 | Abstractive Summarization As Augmentation for Document-Level Event Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we attempt to bridge the performance gap between shallow and deep models on document-level event detection by using abstractive text summarization as an augmentation method. |
Janko Vidaković; Filip Karlo Došilović; Domagoj Pluščec; | arxiv-cs.CL | 2023-05-29 |
185 | An Investigation of Evaluation Metrics for Automated Medical Note Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we study evaluation methods and metrics for the automatic generation of clinical notes from medical conversations. |
Asma Ben Abacha; Wen-wai Yim; George Michalopoulos; Thomas Lin; | arxiv-cs.CL | 2023-05-27 |
186 | Automated Summarization of Stack Overflow Posts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a deep learning based framework called ASSORT for SO post summarization. |
Bonan Kou; Muhao Chen; Tianyi Zhang; | arxiv-cs.SE | 2023-05-26 |
187 | UMSE: Unified Multi-scenario Summarization Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Besides, designing individual models for each scenario caused inconvenience to the user. Inspired by this, we propose Unified Multi-scenario Summarization Evaluation Model (UMSE). |
SHEN GAO et. al. | arxiv-cs.CL | 2023-05-26 |
188 | Domain Aligned Prefix Averaging for Domain Generalization in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a lightweight, weight averaging based, Domain Aligned Prefix Averaging approach to domain generalization for abstractive summarization. |
Pranav Ajit Nair; Sukomal Pal; Pradeepika Verma; | arxiv-cs.CL | 2023-05-26 |
189 | Not All Metrics Are Guilty: Improving NLG Evaluation with LLM Paraphrasing Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The underlying reason is that one semantic meaning can actually be expressed in different forms, and the evaluation with a single or few references may not accurately reflect the quality of the model’s hypotheses. To address this issue, this paper presents a novel method, named Para-Ref, to enhance existing evaluation benchmarks by enriching the number of references. |
TIANYI TANG et. al. | arxiv-cs.CL | 2023-05-24 |
190 | SummIt: Iterative Text Summarization Via ChatGPT IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the one-shot summarization setting is sometimes inadequate, as the generated summary may contain hallucinations or overlook essential details related to the reader’s interests. This paper addresses this limitation by proposing SummIt, an iterative text summarization framework based on large language models like ChatGPT. |
Haopeng Zhang; Xiao Liu; Jiawei Zhang; | arxiv-cs.CL | 2023-05-24 |
191 | Is Summary Useful or Not? An Extrinsic Human Evaluation of Text Summaries on Downstream Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We carefully design three different downstream tasks for extrinsic human evaluation of summaries, i.e., question answering, text classification and text similarity assessment. |
Xiao Pu; Mingqi Gao; Xiaojun Wan; | arxiv-cs.CL | 2023-05-24 |
192 | Peek Across: Improving Multi-Document Modeling Via Cross-Document Question-Answering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The integration of multi-document pre-training objectives into language models has resulted in remarkable improvements in multi-document downstream tasks. In this work, we propose extending this idea by pre-training a generic multi-document model from a novel cross-document question answering pre-training objective. |
Avi Caciularu; Matthew E. Peters; Jacob Goldberger; Ido Dagan; Arman Cohan; | arxiv-cs.CL | 2023-05-24 |
193 | Interpretable Automatic Fine-grained Inconsistency Detection in Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Motivated by how humans inspect factual inconsistency in summaries, we propose an interpretable fine-grained inconsistency detection model, FineGrainFact, which explicitly represents the facts in the documents and summaries with semantic frames extracted by semantic role labeling, and highlights the related semantic frames to predict inconsistency. |
Hou Pong Chan; Qi Zeng; Heng Ji; | arxiv-cs.CL | 2023-05-23 |
194 | USB: A Unified Summarization Benchmark Across Tasks and Domains Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a Wikipedia-derived benchmark, complemented by a rich set of crowd-sourced annotations, that supports $8$ interrelated tasks: (i) extractive summarization; (ii) abstractive summarization; (iii) topic-based summarization; (iv) compressing selected sentences into a one-line summary; (v) surfacing evidence for a summary sentence; (vi) predicting the factual accuracy of a summary sentence; (vii) identifying unsubstantiated spans in a summary sentence; (viii) correcting factual errors in summaries. |
KUNDAN KRISHNA et. al. | arxiv-cs.CL | 2023-05-23 |
195 | On Learning to Summarize with Large Language Models As References IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Therefore, we investigate a new learning setting of text summarization models that considers the LLMs as the reference or the gold-standard oracle on these datasets. To examine the standard practices that are aligned with this new learning setting, we investigate two LLM-based summary quality evaluation methods for model training and adopt a contrastive learning training method to leverage the LLM-guided learning signals. |
YIXIN LIU et. al. | arxiv-cs.CL | 2023-05-23 |
196 | Abstractive Text Summarization Using The BRIO Training Paradigm Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The BRIO training paradigm assumes a non-deterministic distribution to reduce the model’s dependence on reference summaries, and improve model performance during inference. This paper presents a straightforward but effective technique to improve abstractive summaries by fine-tuning pre-trained language models, and training them with the BRIO paradigm. |
Khang Nhut Lam; Thieu Gia Doan; Khang Thua Pham; Jugal Kalita; | arxiv-cs.CL | 2023-05-23 |
197 | Large Language Models Are Not Yet Human-Level Evaluators for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we conduct extensive analysis to investigate the stability and reliability of LLMs as automatic evaluators for abstractive summarization. |
Chenhui Shen; Liying Cheng; Xuan-Phi Nguyen; Yang You; Lidong Bing; | arxiv-cs.CL | 2023-05-22 |
198 | Enhancing Coherence of Extractive Summarization with Multitask Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study proposes a multitask learning architecture for extractive summarization with coherence boosting. |
Renlong Jie; Xiaojun Meng; Lifeng Shang; Xin Jiang; Qun Liu; | arxiv-cs.CL | 2023-05-22 |
199 | Evaluating Factual Consistency of Texts with Semantic Role Labeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce SRLScore, a reference-free evaluation metric designed with text summarization in mind. |
Jing Fan; Dennis Aumiller; Michael Gertz; | arxiv-cs.CL | 2023-05-22 |
200 | Task-agnostic Distillation of Encoder-Decoder Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We examine MiniEnD on language understanding and abstractive summarization. |
Chen Zhang; Yang Yang; Jingang Wang; Dawei Song; | arxiv-cs.CL | 2023-05-20 |
201 | PORTRAIT: A Hybrid APproach TO CReate Extractive Ground-TRuth SummAry for DIsaster EvenT Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, this intuition-based selection of the tweets might lead to a high variance in summaries generated across annotators. Therefore, to handle these challenges, we propose a hybrid (semi-automated) approach (PORTRAIT) where we partly automate the ground-truth summary generation procedure. |
Piyush Kumar Garg; Roshni Chakraborty; Sourav Kumar Dandapat; | arxiv-cs.CL | 2023-05-19 |
202 | Counterfactual Debiasing for Generating Factually Consistent Text Summaries Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Despite substantial progress in abstractive text summarization to generate fluent and informative texts, the factual inconsistency in the generated summaries remains an important … |
Chenhe Dong; Yuexiang Xie; Yaliang Li; Ying Shen; | arxiv-cs.CL | 2023-05-18 |
203 | AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To account for the inherent sequential characteristic of natural language, we introduce Auto-Regressive Diffusion (AR-Diffusion). |
TONG WU et. al. | arxiv-cs.CL | 2023-05-16 |
204 | Legal Extractive Summarization of U.S. Court Opinions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper tackles the task of legal extractive summarization using a dataset of 430K U.S. court opinions with key passages annotated. |
Emmanuel Bauer; Dominik Stammbach; Nianlong Gu; Elliott Ash; | arxiv-cs.CL | 2023-05-15 |
205 | NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we analyze automatic evaluation metrics for Natural Language Generation (NLG), specifically task-agnostic metrics and human-aligned metrics. |
Iftitahu Ni’mah; Meng Fang; Vlado Menkovski; Mykola Pechenizkiy; | arxiv-cs.CL | 2023-05-15 |
206 | Two-in-One: A Model Hijacking Attack Against Text Generation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, this attack has only focused on image classification tasks. In this work, we broaden the scope of this attack to include text generation and classification models, hence showing its broader applicability. |
Wai Man Si; Michael Backes; Yang Zhang; Ahmed Salem; | arxiv-cs.CR | 2023-05-12 |
207 | PROM: A Phrase-level Copying Mechanism with Pre-training for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work proposes PROM, a new PhRase-level cOpying Mechanism that enhances attention on n-grams, which can be applied to zero-shot summarization with pre-training. |
Xinbei Ma; Yeyun Gong; Pengcheng He; Hai Zhao; Nan Duan; | arxiv-cs.CL | 2023-05-11 |
208 | A New Method for Extractive Text Summarization Using Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
S. Chowdhury; K. Sarkar; | SN Computer Science | 2023-05-09 |
209 | Summarization with Precise Length Control Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a framework to generate summaries with precisely the specified number of tokens or sentences, while maintaining or even improving the text quality. |
Lesly Miculicich; Yujia Xie; Song Wang; Pengcheng He; | arxiv-cs.CL | 2023-05-09 |
210 | The Current State of Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work aims to concisely indicate the current state of the art in abstractive text summarization. |
Fabian Retkowski; | arxiv-cs.CL | 2023-05-08 |
211 | Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Generative Pre-trained Transformer 4 (GPT-4) is the fourth-generation language model in the GPT series, developed by OpenAI, which promises significant advancements in the field of natural language processing (NLP). In this research article, we have discussed the features of GPT-4, its potential applications, and the challenges that it might face. |
Jawid Ahmad Baktash; Mursal Dawodi; | arxiv-cs.CL | 2023-05-04 |
212 | Personalized Abstractive Summarization By Tri-agent Generation Pipeline Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a tri-agent generation pipeline comprising a generator, an instructor, and an editor to enhance output personalization. |
Wen Xiao; Yujia Xie; Giuseppe Carenini; Pengcheng He; | arxiv-cs.CL | 2023-05-03 |
213 | Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, this method is constrained by the quality of the fixed corpus from which memory is retrieved. In this paper, by exploring the duality of the primal problem: better generation also prompts better memory, we propose a novel framework, selfmem, which addresses this limitation by iteratively employing a retrieval-augmented generator to create an unbounded memory pool and using a memory selector to choose one output as memory for the subsequent generation round. |
XIN CHENG et. al. | arxiv-cs.CL | 2023-05-03 |
214 | Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose TempoSum, a novel benchmark that contains data samples from 2010 to 2022, to understand the temporal generalization ability of abstractive summarization models. |
CHI SENG CHEANG et. al. | arxiv-cs.CL | 2023-05-03 |
215 | Backdoor Learning on Sequence to Sequence Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study a much more challenging problem of testing whether sequence-to-sequence (seq2seq) models are vulnerable to backdoor attacks. |
Lichang Chen; Minhao Cheng; Heng Huang; | arxiv-cs.CL | 2023-05-03 |
216 | DiffuSum: Generation Enhanced Extractive Summarization with Diffusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes DiffuSum, a novel paradigm for extractive summarization, by directly generating the desired summary sentence representations with diffusion models and extracting sentences based on sentence representation matching. |
Haopeng Zhang; Xiao Liu; Jiawei Zhang; | arxiv-cs.CL | 2023-05-02 |
217 | Enhanced Sentence Representation for Extractive Text Summarization: Investigating The Syntactic and Semantic Features and Their Contribution to Sentence Scoring Related Papers Related Patents Related Grants Related Venues Related Experts View |
Begum Mutlu; E. Sezer; | Expert Syst. Appl. | 2023-05-01 |
218 | HISum: Hyperbolic Interaction Model for Extractive Multi-Document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new hyperbolic interaction model for extractive multi-document summarization (HISum). |
Mingyang Song; Yi Feng; Liping Jing; | www | 2023-04-29 |
219 | XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Hence, in this work, we propose XWikiGen, which is the task of cross-lingual multi-document summarization of text from multiple reference articles, written in various languages, to generate Wikipedia-style text. |
DHAVAL TAUNK et. al. | www | 2023-04-29 |
220 | Towards Understanding Consumer Healthcare Questions on The Web with Semantically Enhanced Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a semantically-enhanced contrastive learning-based framework for generating abstractive question summaries that are faithful and factually correct. |
Shweta Yadav; Ștefan Cobeli; Cornelia Caragea; | www | 2023-04-29 |
221 | ChatGPT in The Classroom: An Analysis of Its Strengths and Weaknesses for Solving Undergraduate Computer Science Questions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper adopts a quantitative approach to demonstrate ChatGPT’s high degree of unreliability in answering a diverse range of questions pertaining to topics in undergraduate computer science. |
ISHIKA JOSHI et. al. | arxiv-cs.HC | 2023-04-28 |
222 | Unsupervised Extractive Summarization With Heterogeneous Graph Embeddings for Chinese Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we are the first to propose an unsupervised extractive summarizaiton method with heterogeneous graph embeddings (HGEs) for Chinese documents. |
C. Lin; Y. Liu; S. An; D. Yin; | icassp | 2023-04-27 |
223 | Leveraging Large Text Corpora For End-To-End Speech Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present two novel methods that leverage a large amount of external text summarization data for E2E SSum training. |
K. MATSUURA et. al. | icassp | 2023-04-27 |
224 | Boosting Big Brother: Attacking Search Engines with Encodings Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We also present a variant of the attack targeting text summarization and plagiarism detection models, two ML tasks closely tied to search. We provide a set of defenses against these techniques and warn that adversaries can leverage these attacks to launch disinformation campaigns against unsuspecting users, motivating the need for search engine maintainers to patch deployed systems. |
Nicholas Boucher; Luca Pajola; Ilia Shumailov; Ross Anderson; Mauro Conti; | arxiv-cs.CR | 2023-04-27 |
225 | Attention Localness in Shared Encoder-Decoder Model For Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a localness attention network, with simplicity and feasibility in mind, which circles different local regions in the source article as contributors in different decoding steps. |
L. Huang; H. Wu; Q. Gao; G. Liu; | icassp | 2023-04-27 |
226 | PyBibX — A Python Library for Bibliometric and Scientometric Analysis Powered with Artificial Intelligence Tools Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Bibliometric and Scientometric analyses offer invaluable perspectives on the complex research terrain and collaborative dynamics spanning diverse academic disciplines. This paper presents pyBibX, a python library devised to conduct comprehensive bibliometric and scientometric analyses on raw data files sourced from Scopus, Web of Science, and PubMed, seamlessly integrating state of the art AI capabilities into its core functionality. |
Valdecy Pereira; Marcio Pereira Basilio; Carlos Henrique Tarjano Santos; | arxiv-cs.DL | 2023-04-27 |
227 | Post-Trained Language Model Adaptive to Extractive Summarization of Long Spoken Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a post-trained DeBERTA which does not only adapt to spoken language but also manages long documents. |
H. Ok; S. -B. Park; | icassp | 2023-04-27 |
228 | Improving Sentence Similarity Estimation for Unsupervised Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we proposed two novel strategies to improve sentence similarity estimation for unsupervised extractive summarization. |
S. Sun; R. Yuan; W. Li; S. Li; | icassp | 2023-04-27 |
229 | MUG: A General Meeting Understanding and Generation Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To the best of our knowledge, the AliMeeting4MUG Corpus is so far the largest meeting corpus in scale and facilitates most SLP tasks. In this paper, we provide a detailed introduction of this corpus, SLP tasks and evaluation methods, baseline systems and their performance1. |
Q. ZHANG et. al. | icassp | 2023-04-27 |
230 | Speech Summarization of Long Spoken Document: Improving Memory Efficiency of Speech/Text Encoders Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a speech summarization system that enables E2E summarization from 100 seconds, which is the limit of the conventional method, to up to 10 minutes (i.e., the duration of typical instructional videos on YouTube). |
T. KANO et. al. | icassp | 2023-04-27 |
231 | ChartSumm: A Comprehensive Benchmark for Automatic Chart Summarization of Long and Short Summaries Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose ChartSumm: a large-scale benchmark dataset consisting of a total of 84,363 charts along with their metadata and descriptions covering a wide range of topics and chart types to generate short and long summaries. |
RAIAN RAHMAN et. al. | arxiv-cs.CL | 2023-04-26 |
232 | Personalized Federated Learning Via Gradient Modulation for Heterogeneous Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose FedSUMM, a dynamic gradient adapter to provide more appropriate local parameters for local model. |
Rongfeng Pan; Jianzong Wang; Lingwei Kong; Zhangcheng Huang; Jing Xiao; | arxiv-cs.AI | 2023-04-22 |
233 | Evaluation of Automatic Legal Text Summarization Techniques for Greek Case Law Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The increasing amount of legal information available online is overwhelming for both citizens and legal professionals, making it difficult and time-consuming to find relevant … |
Marios Koniaris; Dimitris Galanis; E. Giannini; P. Tsanakas; | Inf. | 2023-04-21 |
234 | A Survey on Biomedical Text Summarization with Pre-trained Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we systematically summarize recent advances that explore PLMs for biomedical text summarization, to help understand recent progress, challenges, and future directions. |
Qianqian Xie; Zheheng Luo; Benyou Wang; Sophia Ananiadou; | arxiv-cs.CL | 2023-04-18 |
235 | Just Tell Me: Prompt Engineering in Business Process Management Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: GPT-3 and several other language models (LMs) can effectively address various natural language processing (NLP) tasks, including machine translation and text summarization. |
Kiran Busch; Alexander Rochlitzer; Diana Sola; Henrik Leopold; | arxiv-cs.AI | 2023-04-14 |
236 | Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: If they aren’t, could explicitly adding this information help? Our goal here is to investigate this question, using the code summarization task and evaluate whether automatically augmenting an LLM’s prompt with semantic facts explicitly, actually helps. |
Toufique Ahmed; Kunal Suresh Pai; Premkumar Devanbu; Earl T. Barr; | arxiv-cs.SE | 2023-04-13 |
237 | Extractive Summarization Via ChatGPT for Faithful Summary Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, we find that applying an extract-then-generate pipeline with ChatGPT yields significant performance improvements over abstractive baselines in terms of summary faithfulness. These observations highlight potential directions for enhancing ChatGPT’s capabilities in faithful summarization using two-stage approaches. |
Haopeng Zhang; Xiao Liu; Jiawei Zhang; | arxiv-cs.CL | 2023-04-09 |
238 | GEMINI: Controlling The Sentence-level Writing Style for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: These techniques are flexible and thus difficult to be imitated by any single method. To address this issue, we propose an adaptive model, GEMINI, that integrates a rewriter and a generator to mimic the sentence rewriting and abstracting techniques, respectively. |
Guangsheng Bao; Zebin Ou; Yue Zhang; | arxiv-cs.CL | 2023-04-07 |
239 | Human-like Summarization Evaluation with ChatGPT IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we explored ChatGPT’s ability to perform human-like summarization evaluation using four human evaluation methods on five datasets. |
MINGQI GAO et. al. | arxiv-cs.CL | 2023-04-05 |
240 | San-BERT: Extractive Summarization for Sanskrit Documents Using BERT and It’s Variants Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we develop language models for the Sanskrit language, namely Bidirectional Encoder Representations from Transformers (BERT) and its variants: A Lite BERT (ALBERT), and Robustly Optimized BERT (RoBERTa) using Devanagari Sanskrit text corpus. |
Kartik Bhatnagar; Sampath Lonka; Jammi Kunal; Mahabala Rao M G; | arxiv-cs.CL | 2023-04-04 |
241 | SimCSum: Joint Learning of Simplification and Cross-lingual Summarization for Cross-lingual Science Journalism Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel multi-task architecture – SimCSum consisting of one shared encoder and two parallel decoders jointly learning simplification and cross-lingual summarization. |
Mehwish Fatima; Tim Kolber; Katja Markert; Michael Strube; | arxiv-cs.CL | 2023-04-04 |
242 | A Comparison of Document Similarity Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This report sets out to examine the numerous document similarity algorithms, and determine which ones are the most useful. |
Nicholas Gahman; Vinayak Elangovan; | arxiv-cs.CL | 2023-04-03 |
243 | CQSumDP: A ChatGPT-Annotated Resource for Query-Focused Abstractive Summarization Based on Debatepedia Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Debatepedia is a publicly available dataset consisting of arguments and counter-arguments on controversial topics that has been widely used for the single-document query-focused … |
Md Tahmid Rahman Laskar; Mizanur Rahman; Israt Jahan; Enamul Hoque; J. Huang; | ArXiv | 2023-03-31 |
244 | Comparing Abstractive Summaries Generated By ChatGPT to Real Summaries Through Blinded Reviewers and Text Classification Algorithms IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We found that while text classification algorithms can distinguish between real and generated summaries, humans are unable to distinguish between real summaries and those produced by ChatGPT. |
Mayank Soni; Vincent Wade; | arxiv-cs.CL | 2023-03-30 |
245 | ChatGPT As A Factual Inconsistency Evaluator for Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we particularly explore ChatGPT’s ability to evaluate factual inconsistency under a zero-shot setting by examining it on both coarse-grained and fine-grained evaluation tasks including binary entailment inference, summary ranking, and consistency rating. |
Zheheng Luo; Qianqian Xie; Sophia Ananiadou; | arxiv-cs.CL | 2023-03-27 |
246 | Large Language Models Are Diverse Role-Players for Summarization Evaluation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new evaluation framework based on LLMs, which provides a comprehensive evaluation framework by comparing generated text and reference text from both objective and subjective aspects. |
Ning Wu; Ming Gong; Linjun Shou; Shining Liang; Daxin Jiang; | arxiv-cs.CL | 2023-03-27 |
247 | Indian Language Summarization Using Pretrained Sequence-to-Sequence Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a detailed overview of the models and our approaches in this paper. |
Ashok Urlana; Sahil Manoj Bhatt; Nirmal Surange; Manish Shrivastava; | arxiv-cs.CL | 2023-03-25 |
248 | SASS: Data and Methods for Subject Aware Sentence Simplification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper provides a dataset aimed at training models that perform subject aware sentence simplifications rather than simplifying sentences as a whole. |
Brad Windsor; Luke Martin; Anand Tyagi; | arxiv-cs.CL | 2023-03-25 |
249 | MUG: A General Meeting Understanding and Generation Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To the best of our knowledge, the AliMeeting4MUG Corpus is so far the largest meeting corpus in scale and facilitates most SLP tasks. In this paper, we provide a detailed introduction of this corpus, SLP tasks and evaluation methods, baseline systems and their performance. |
QINGLIN ZHANG et. al. | arxiv-cs.CL | 2023-03-24 |
250 | Overview of The ICASSP 2023 General Meeting Understanding and Generation Challenge (MUG) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To facilitate MUG, we construct and release a large-scale meeting dataset, the AliMeeting4MUG Corpus. |
QINGLIN ZHANG et. al. | arxiv-cs.CL | 2023-03-24 |
251 | SPEC: Summary Preference Decomposition for Low-Resource Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the problems of learning summarizers with only few examples and propose corresponding methods for improvements. |
Yi-Syuan Chen; Yun-Zhu Song; Hong-Han Shuai; | arxiv-cs.CL | 2023-03-24 |
252 | Lay Text Summarisation Using Natural Language Processing: A Narrative Literature Review Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The use of Natural Language Processing to generate lay summaries has the potential to relieve researchers’ workload and bridge the gap between science and society. The aim of this narrative literature review is to describe and compare the different text summarisation approaches used to generate lay summaries. |
Oliver Vinzelberg; Mark David Jenkins; Gordon Morison; David McMinn; Zoe Tieges; | arxiv-cs.CL | 2023-03-24 |
253 | VideoXum: Cross-modal Visual and Textural Summarization of Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new joint video and text summarization task. |
JINGYANG LIN et. al. | arxiv-cs.CV | 2023-03-21 |
254 | Exploring The Feasibility of ChatGPT for Event Extraction IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To explore the feasibility of ChatGPT for event extraction and the challenges it poses, we conducted a series of experiments. |
Jun Gao; Huan Zhao; Changlong Yu; Ruifeng Xu; | arxiv-cs.CL | 2023-03-07 |
255 | Faithfulness-Aware Decoding Strategies for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose two faithfulness-aware generation methods to further improve faithfulness over current generation techniques: (1) ranking candidates generated by beam search using automatic faithfulness metrics and (2) incorporating lookahead heuristics that produce a faithfulness score on the future summary. |
David Wan; Mengwen Liu; Kathleen McKeown; Markus Dreyer; Mohit Bansal; | arxiv-cs.CL | 2023-03-06 |
256 | Leveraging Large Text Corpora for End-to-End Speech Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present two novel methods that leverage a large amount of external text summarization data for E2E SSum training. |
KOHEI MATSUURA et. al. | arxiv-cs.CL | 2023-03-02 |
257 | Arabic Abstractive Text Summarization Using RNN-based and Transformer-based Architectures Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mohammad Bani-Almarjeh; M. Kurdy; | Inf. Process. Manag. | 2023-03-01 |
258 | Uzbek Text Summarization Based on TF-IDF Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article presents an experiment on summarization task for Uzbek language, the methodology was based on text abstracting based on TF-IDF algorithm. |
Khabibulla Madatov; Shukurla Bekchanov; Jernej Vičič; | arxiv-cs.CL | 2023-03-01 |
259 | Efficient Informed Proposals for Discrete Distributions Via Newton’s Series Approximation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these methods require a natural differentiable extension of the target discrete distribution, which often does not exist or does not provide effective gradient guidance. In this paper, we develop a gradient-like proposal for any discrete distribution without this strong requirement. |
Yue Xiang; Dongyao Zhu; Bowen Lei; Dongkuan Xu; Ruqi Zhang; | arxiv-cs.LG | 2023-02-27 |
260 | Abstractive Text Summarization Using Attentive GRU Based Encoder-Decoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, an english text summarizer has been built with GRU-based encoder and decoder. |
Tohida Rehman; Suchandan Das; Debarshi Kumar Sanyal; Samiran Chattopadhyay; | arxiv-cs.CL | 2023-02-25 |
261 | An Analysis of Abstractive Text Summarization Using Pre-trained Models Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tohida Rehman; S. Das; Debarshi Kumar Sanyal; S. Chattopadhyay; | ArXiv | 2023-02-25 |
262 | Improving Sentence Similarity Estimation for Unsupervised Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we proposed two novel strategies to improve sentence similarity estimation for unsupervised extractive summarization. |
Shichao Sun; Ruifeng Yuan; Wenjie Li; Sujian Li; | arxiv-cs.CL | 2023-02-24 |
263 | Summaries As Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we show that it can be more effectively tackled as a text summarization task in scientific documents. |
CHIEH-YANG HUANG et. al. | arxiv-cs.CL | 2023-02-23 |
264 | Learning with Rejection for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a training objective for abstractive summarization based on rejection learning, in which the model learns whether or not to reject potentially noisy tokens. |
Meng Cao; Yue Dong; Jingyi He; Jackie Chi Kit Cheung; | arxiv-cs.CL | 2023-02-16 |
265 | Exploring The Limits of ChatGPT for Query or Aspect-based Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Various methods have been proposed for text summarization, including extractive and abstractive summarization. |
Xianjun Yang; Yan Li; Xinlu Zhang; Haifeng Chen; Wei Cheng; | arxiv-cs.CL | 2023-02-15 |
266 | Exploiting Summarization Data to Help Text Simplification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we analyzed the similarity between text summarization and text simplification and exploited summarization data to help simplify. |
Renliang Sun; Zhixian Yang; Xiaojun Wan; | arxiv-cs.CL | 2023-02-14 |
267 | Leveraging Summary Guidance on Medical Report Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50K, 16K and 378K pairs of report and summary that are derived from MIMIC-III, respectively. |
Yunqi Zhu; Xuebing Yang; Yuanyuan Wu; Wensheng Zhang; | arxiv-cs.CL | 2023-02-08 |
268 | Long Text and Multi-Table Summarization: Dataset and Method Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To summarize the long text and dozens of tables in each report, we present three types of summarization methods. |
Shuaiqi Liu; Jiannong Cao; Ruosong Yang; Zhiyuan Wen; | arxiv-cs.CL | 2023-02-07 |
269 | An Entity-guided Text Summarization Framework with Relational Heterogeneous Graph Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper focuses on both issues by leveraging entities mentioned in text to connect GNN and KG for summarization. |
Jingqiang Chen; | arxiv-cs.CL | 2023-02-06 |
270 | Enhancing Metaheuristic Based Extractive Text Summarization with Fuzzy Logic Related Papers Related Patents Related Grants Related Venues Related Experts View |
Minakshi Tomer; M. Kumar; A. Hashmi; Bharti Sharma; U. Tomer; | Neural Computing and Applications | 2023-02-02 |
271 | Curriculum-Guided Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nonetheless, these models have two shortcomings: (1) they often perform poorly in content selection, and (2) their training strategy is not quite efficient, which restricts model performance. In this paper, we explore two orthogonal ways to compensate for these pitfalls. |
Sajad Sotudeh; Hanieh Deilamsalehy; Franck Dernoncourt; Nazli Goharian; | arxiv-cs.CL | 2023-02-02 |
272 | Curriculum-guided Abstractive Summarization for Mental Health Online Posts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we include a curriculum learning approach to reweigh the training samples, bringing about an efficient learning procedure. |
Sajad Sotudeh; Nazli Goharian; Hanieh Deilamsalehy; Franck Dernoncourt; | arxiv-cs.CL | 2023-02-02 |
273 | Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a combination of retrieval, reranking, and the well-known Integer Linear Programming (ILP) and Maximal Marginal Relevance (MMR) frameworks. |
Philipp Seeberger; Korbinian Riedhammer; | arxiv-cs.CL | 2023-02-02 |
274 | Text Summarization with Oracle Expectation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we identify two flaws with the widely used greedy labeling approach: it delivers suboptimal and deterministic oracles. |
Yumo Xu; Mirella Lapata; | iclr | 2023-02-01 |
275 | Out-of-Distribution Detection and Selective Generation for Conditional Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, the space of potential low-quality outputs is larger as arbitrary text can be generated and it is important to know when to trust the generated output. We present a highly accurate and lightweight OOD detection method for CLMs, and demonstrate its effectiveness on abstractive summarization and translation. |
JIE REN et. al. | iclr | 2023-02-01 |
276 | HunSum-1: An Abstractive Summarization Dataset for Hungarian Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce HunSum-1: a dataset for Hungarian abstractive summarization, consisting of 1.14M news articles. |
Botond Barta; Dorina Lakatos; Attila Nagy; Milán Konor Nyist; Judit Ács; | arxiv-cs.CL | 2023-02-01 |
277 | Calibrating Sequence Likelihood Improves Conditional Language Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce sequence likelihood calibration (SLiC) where the likelihood of model generated sequences are calibrated to better align with reference sequences in the model’s latent space. |
YAO ZHAO et. al. | iclr | 2023-02-01 |
278 | LoRaLay: A Multilingual and Multimodal Dataset for Long Range and Layout-Aware Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To facilitate research on how to exploit visual/layout information to better capture long-range dependencies in summarization models, we present LoRaLay, a collection of datasets for long-range summarization with accompanying visual/layout information. |
Laura Nguyen; Thomas Scialom; Benjamin Piwowarski; Jacopo Staiano; | arxiv-cs.CL | 2023-01-26 |
279 | Language-independent Extractive Automatic Text Summarization Based on Automatic Keyword Extraction IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ángel Hernández-Castañeda; René Arnulfo García-Hernández; Yulia Ledeneva; Christian Eduardo Millán-Hernández; | Comput. Speech Lang. | |
280 | Document Summarization with Text Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we exploit the innate document segment structure for improving the extractive summarization task. |
Lesly Miculicich; Benjamin Han; | arxiv-cs.CL | 2023-01-20 |
281 | Transformer Based Implementation for Automatic Book Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work is an attempt to use Transformer based techniques for Abstract generation. |
Siddhant Porwal; Laxmi Bewoor; Vivek Deshpande; | arxiv-cs.CL | 2023-01-17 |
282 | On The State of German (Abstractive) Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we assess the particular landscape of German abstractive text summarization and investigate the reasons why practically useful solutions for abstractive text summarization are still absent in industry. |
Dennis Aumiller; Jing Fan; Michael Gertz; | arxiv-cs.CL | 2023-01-17 |
283 | Active Learning for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This stems from the fact that many AL strategies rely on uncertainty estimation, while as we show in our work, uncertain instances are usually noisy, and selecting them can degrade the model performance compared to passive annotation. We address this problem by proposing the first effective query strategy for AL in ATS based on diversity principles. |
AKIM TSVIGUN et. al. | arxiv-cs.CL | 2023-01-09 |
284 | A Comprehensive Review of Automatic Text Summarization Techniques: Method, Data, Evaluation and Coding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We start with some popular and well-known papers that we have in hand about each topic we want to cover and we have tracked the backward citations (papers that are cited by the set of papers we knew beforehand) and the forward citations (newer papers that cite the set of papers we knew beforehand). In order to organize the different methods, we present the diverse approaches to ATS guided by the mechanisms they use to generate a summary. |
DANIEL O. CAJUEIRO et. al. | arxiv-cs.CL | 2023-01-04 |
285 | Follow The Timeline! Generating Abstractive and Extractive Timeline Summary in Chronological Order Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unlike traditional document summarization, timeline summarization needs to model the time series information of the input events and summarize important events in chronological order. To tackle this challenge, in this paper, we propose a Unified Timeline Summarizer (UTS) that can generate abstractive and extractive timeline summaries in time order. |
XIUYING CHEN et. al. | arxiv-cs.CL | 2023-01-02 |
286 | MLASK: Multimodal Summarization of Video-based News Articles Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, the pattern of news consumption has been changing. The most popular multimedia news formats are now multimodal – the reader is often presented not only with a … |
Mateusz Krubiński; Pavel Pecina; | Findings | 2023-01-01 |
287 | ChatGPT As A Factual Inconsistency Evaluator for Abstractive Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The performance of abstractive text summarization has been greatly boosted by pre-trained language models recently. The main concern of existing abstractive summarization methods … |
Zheheng Luo; Qianqian Xie; S. Ananiadou; | ArXiv | 2023-01-01 |
288 | Token-Level Fact Correction in Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper addresses fact correction for abstractive summarization of which aim is to edit a system-generated summary into a new source-consistent summary. The summaries generated … |
Jeongwan Shin; Seong-Bae Park; Hyun-Je Song; | IEEE Access | 2023-01-01 |
289 | Enhancing Multi-Document Summarization with Cross-Document Graph-based Information Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Information extraction (IE) and summarization are closely related, both tasked with presenting a subset of the information contained in a natural language text. However, while IE … |
ZIXUAN ZHANG et. al. | Conference of the European Chapter of the Association for … | 2023-01-01 |
290 | Binary Particle Swarm Optimization with An Improved Genetic Algorithm to Solve Multi-document Text Summarization Problem of Hindi Documents Related Papers Related Patents Related Grants Related Venues Related Experts View |
S. Aote; Anjusha Pimpalshende; A. Potnurwar; S. Lohi; | Eng. Appl. Artif. Intell. | 2023-01-01 |
291 | Multilingual Summarization with Factual Consistency Evaluation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization has enjoyed re-newed interest in recent years, thanks to pre-trained language models and the availability of large-scale datasets. Despite promising … |
ROEE AHARONI et. al. | Annual Meeting of the Association for Computational … | 2023-01-01 |
292 | When Do Pre-Training Biases Propagate to Downstream Tasks? A Case Study in Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large language models (LLMs) are subject to sociocultural and other biases previously identified using intrinsic evaluations. However, when and how these intrinsic biases in … |
FAISAL LADHAK et. al. | Conference of the European Chapter of the Association for … | 2023-01-01 |
293 | READSUM: Retrieval-Augmented Adaptive Transformer for Source Code Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Code summarization is the process of automatically generating brief and informative summaries of source code to aid in software comprehension and maintenance. In this paper, we … |
YunSeok Choi; CheolWon Na; Hyojun Kim; Jee-Hyong Lee; | IEEE Access | 2023-01-01 |
294 | STRUDEL: Structured Dialogue Summarization for Dialogue Comprehension Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel type of dialogue summarization task – STRUctured DiaLoguE Summarization (STRUDEL) – that can help pre-trained language models to better understand dialogues and improve their performance on important dialogue comprehension tasks. |
BORUI WANG et. al. | emnlp | 2022-12-30 |
295 | Salience Allocation As Guidance for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel summarization approach with a flexible and reliable salience guidance, namely SEASON (SaliencE Allocation as Guidance for Abstractive SummarizatiON). |
FEI WANG et. al. | emnlp | 2022-12-30 |
296 | Evaluating and Improving Factuality in Multimodal Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose CLIPBERTSCORE, a simple weighted combination of CLIPScore and BERTScore to leverage the robustness and strong factuality detection performance between image-summary and document-summary, respectively. |
David Wan; Mohit Bansal; | emnlp | 2022-12-30 |
297 | Towards Summary Candidates Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To bypass this limitation, we propose a new paradigm in second-stage abstractive summarization called SummaFusion that fuses several summary candidates to produce a novel abstractive second-stage summary. |
Mathieu Ravaut; Shafiq Joty; Nancy Chen; | emnlp | 2022-12-30 |
298 | HydraSum: Disentangling Style Features in Text Summarization with Multi-Decoder Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, these are implicitly encoded within model parameters and specific styles cannot be enforced. To address this, we introduce HydraSum, a new summarization architecture that extends the single decoder framework of current models to a mixture-of-experts version with multiple decoders. |
Tanya Goyal; Nazneen Rajani; Wenhao Liu; Wojciech Kryscinski; | emnlp | 2022-12-30 |
299 | Towards A Unified Multi-Dimensional Evaluator for Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a unified multi-dimensional evaluator UniEval for NLG. |
MING ZHONG et. al. | emnlp | 2022-12-30 |
300 | SEM-F1: An Automatic Way for Semantic Evaluation of Multi-Narrative Overlap Summaries at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we exclusively focus on the automated evaluation of the SOS task using the benchmark dataset. |
Naman Bansal; Mousumi Akter; Shubhra Kanti Karmaker Santu; | emnlp | 2022-12-30 |
301 | Improving Faithfulness By Augmenting Negative Summaries from Fake Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the commonly used maximum likelihood training does not disentangle factual errors from other model errors. To address this issue,we propose a back-translation-style approach to augment negative samples that mimic factual errors made by the model. |
Tianshu Wang; Faisal Ladhak; Esin Durmus; He He; | emnlp | 2022-12-30 |
302 | Few-shot Query-Focused Summarization with Prefix-Merging Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the idea that whether we can integrate and transfer the knowledge of text summarization and question answering to assist the few-shot learning in query-focused summarization. |
Ruifeng Yuan; Zili Wang; Ziqiang Cao; Wenjie Li; | emnlp | 2022-12-30 |
303 | Unsupervised Opinion Summarisation in The Wasserstein Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Such posts are noisy and have unpredictable structure, posing additional challenges for the construction of the summary distribution and the preservation of meaning compared to online reviews, which has been so far the focus on opinion summarisation. To address these challenges we present WassOS, an unsupervised abstractive summarization model which makesuse of the Wasserstein distance. |
Jiayu Song; Iman Munire Bilal; Adam Tsakalidis; Rob Procter; Maria Liakata; | emnlp | 2022-12-30 |
304 | X-FACTOR: A Cross-metric Evaluation of Factual Correctness in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present X-FACTOR, a cross-evaluation of three high-performing fact-aware abstractive summarization methods. |
SUBHAJIT CHAUDHURY et. al. | emnlp | 2022-12-30 |
305 | Mutual Information Alleviates Hallucinations in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we identify a simple criterion under which models are significantly more likely to assign more probability to hallucinated content during generation: high model uncertainty. |
Liam van der Poel; Ryan Cotterell; Clara Meister; | emnlp | 2022-12-30 |
306 | Scientific Paper Extractive Summarization Enhanced By Citation Graphs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on leveraging citation graphs to improve scientific paper extractive summarization under different settings. |
XIUYING CHEN et. al. | emnlp | 2022-12-30 |
307 | Analyzing and Evaluating Faithfulness in Dialogue Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we first perform the fine-grained human analysis on the faithfulness of dialogue summaries and observe that over 35% of generated summaries are faithfully inconsistent respective the source dialogues. Furthermore, we present a new model-level faithfulness evaluation method. |
Bin Wang; Chen Zhang; Yan Zhang; Yiming Chen; Haizhou Li; | emnlp | 2022-12-30 |
308 | Leveraging Locality in Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the quadratic memory complexity of the self-attention module with respect to the input length hinders their applications in long text summarization. Instead of designing more efficient attention modules, we approach this problem by investigating if models with a restricted context can have competitive performance compared with the memory-efficient attention models that maintain a global context by treating the input as a single sequence. |
YIXIN LIU et. al. | emnlp | 2022-12-30 |
309 | R-TeaFor: Regularized Teacher-Forcing for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Nevertheless, they do not consider the pairwise relationship between the original training data and the modified ones, which provides more information during training. Hence, we propose Regularized Teacher-Forcing (R-TeaFor) to utilize this relationship for better regularization. |
Guan-Yu Lin; Pu-Jen Cheng; | emnlp | 2022-12-30 |
310 | Correcting Diverse Factual Errors in Abstractive Summarization Via Post-Editing and Language Model Infilling IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to generate hard, representative synthetic examples of non-factual summaries through infilling language models. |
Vidhisha Balachandran; Hannaneh Hajishirzi; William Cohen; Yulia Tsvetkov; | emnlp | 2022-12-30 |
311 | Questioning The Validity of Summarization Datasets and Improving Their Factual Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to this lack of well-defined formulation, a large number of popular abstractive summarization datasets are constructed in a manner that neither guarantees validity nor meets one of the most essential criteria of summarization: factual consistency. In this paper, we address this issue by combining state-of-the-art factual consistency models to identify the problematic instances present in popular summarization datasets. |
Yanzhu Guo; Chlo� Clavel; Moussa Kamal Eddine; Michalis Vazirgiannis; | emnlp | 2022-12-30 |
312 | Summarizing Community-based Question-Answer Pairs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To help users quickly digest the key information, we propose the novel CQA summarization task that aims to create a concise summary from CQA pairs. |
Ting-Yao Hsu; Yoshi Suhara; Xiaolan Wang; | emnlp | 2022-12-30 |
313 | Human Guided Exploitation of Interpretable Attention Patterns in Summarization and Topic Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In another vein, researchers propose new attention augmentation methods to make transformers more accurate, efficient and interpretable. In this paper, we combine these two lines of research in a human-in-the-loop pipeline to first discover important task-specific attention patterns. |
RAYMOND LI et. al. | emnlp | 2022-12-30 |
314 | CTRLsum: Towards Generic Controllable Text Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Current summarization systems yield generic summaries that are disconnected from users? preferences and expectations. To address this limitation, we present CTRLsum, a generic framework to control generated summaries through a set of keywords. |
Junxian He; Wojciech Kryscinski; Bryan McCann; Nazneen Rajani; Caiming Xiong; | emnlp | 2022-12-30 |
315 | Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We argue that disentangling content selection from the budget used to cover salient content improves the performance and applicability of abstractive summarizers. |
Marcio Fonseca; Yftah Ziser; Shay B. Cohen; | emnlp | 2022-12-30 |
316 | HEGEL: Hypergraph Transformer for Long Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes HEGEL, a hypergraph neural network for long document summarization by capturing high-order cross-sentence relations. |
Haopeng Zhang; Xiao Liu; Jiawei Zhang; | emnlp | 2022-12-30 |
317 | Toward Unifying Text Segmentation and Long Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we explore the role that section segmentation plays in extractive summarization of written and spoken documents. |
Sangwoo Cho; Kaiqiang Song; Xiaoyang Wang; Fei Liu; Dong Yu; | emnlp | 2022-12-30 |
318 | Abstractive Summarization Guided By Latent Hierarchical Document Structure Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this shortcoming, we propose a hierarchy-aware graph neural network (HierGNN) which captures such dependencies through three main steps: 1) learning a hierarchical document structure through a latent structure tree learned by a sparse matrix-tree computation; 2) propagating sentence information over this structure using a novel message-passing node propagation mechanism to identify salient information; 3) using graph-level attention to concentrate the decoder on salient information. |
Yifu Qiu; Shay B. Cohen; | emnlp | 2022-12-30 |
319 | How Far Are We from Robust Long Abstractive Summarization? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Abstractive summarization has made tremendous progress in recent years. In this work, we perform fine-grained human annotations to evaluate long document abstractive summarization systems (i.e., models and metrics) with the aim of implementing them to generate reliable summaries. |
Huan Yee Koh; Jiaxin Ju; He Zhang; Ming Liu; Shirui Pan; | emnlp | 2022-12-30 |
320 | Linearizing Transformer with Key-Value Memory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Memsizer, an approach towards closing the performance gap while improving the efficiency even with short generation. |
Yizhe Zhang; Deng Cai; | emnlp | 2022-12-30 |
321 | Controlled Text Reduction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Concretely, we formalize Controlled Text Reduction as a standalone task, whose input is a source text with marked spans of targeted content (?highlighting?). |
Aviv Slobodkin; Paul Roit; Eran Hirsch; Ori Ernst; Ido Dagan; | emnlp | 2022-12-30 |
322 | BART-IT: An Efficient Sequence-to-Sequence Model for Italian Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: The emergence of attention-based architectures has led to significant improvements in the performance of neural sequence-to-sequence models for text summarization. Although these … |
Moreno La Quatra; Luca Cagliero; | Future Internet | 2022-12-27 |
323 | GAE-ISumm: Unsupervised Graph-Based Summarization of Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose GAE-ISumm, an unsupervised Indic summarization model that extracts summaries from text documents. |
Lakshmi Sireesha Vakada; Anudeep Ch; Mounika Marreddy; Subba Reddy Oota; Radhika Mamidi; | arxiv-cs.CL | 2022-12-25 |
324 | Generating Multiple-Length Summaries Via Reinforcement Learning for Unsupervised Sentence Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we devise an abstractive model based on reinforcement learning without ground-truth summaries. |
Dongmin Hyun; Xiting Wang; Chanyoung Park; Xing Xie; Hwanjo Yu; | arxiv-cs.CL | 2022-12-21 |
325 | OpineSum: Entailment-based Self-training for Abstractive Opinion Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a novel self-training approach, OpineSum, for abstractive opinion summarization. |
Annie Louis; Joshua Maynez; | arxiv-cs.CL | 2022-12-21 |
326 | EIT: Enhanced Interactive Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel architecture, the Enhanced Interactive Transformer (EIT), to address the issue of head degradation in self-attention mechanisms. |
Tong Zheng; Bei Li; Huiwen Bao; Tong Xiao; Jingbo Zhu; | arxiv-cs.CL | 2022-12-20 |
327 | Toward Human-Like Evaluation for Natural Language Generation with Error Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: The state-of-the-art language model-based automatic metrics, e.g. BARTScore, benefiting from large-scale contextualized pre-training, have been successfully used in a wide range … |
QINGYU LU et. al. | arxiv-cs.CL | 2022-12-20 |
328 | Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Given the challenge behind interpretable learning-based text summarization and the importance it may have for evolving the current state of the ATS field, this work studies the application of two modern Generalized Additive Models with interactions, namely Explainable Boosting Machine and GAMI-Net, to the extractive summarization problem based on linguistic features and binary classification. |
Vinícius Camargo da Silva; João Paulo Papa; Kelton Augusto Pontara da Costa; | arxiv-cs.CL | 2022-12-20 |
329 | MFACE: Multilingual Summarization with Factual Consistency Evaluation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we leverage factual consistency evaluation models to improve multilingual summarization. |
ROEE AHARONI et. al. | arxiv-cs.CL | 2022-12-20 |
330 | Very Large Language Model As A Unified Methodology of Text Mining Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, I present a blue sky idea that very large language model (VLLM) will become an effective unified methodology of text mining. |
Meng Jiang; | arxiv-cs.DB | 2022-12-19 |
331 | Unsupervised Summarization Re-ranking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to re-rank summary candidates in an unsupervised manner, aiming to close the performance gap between unsupervised and supervised models. |
Mathieu Ravaut; Shafiq Joty; Nancy Chen; | arxiv-cs.CL | 2022-12-19 |
332 | Improving Faithfulness of Abstractive Summarization By Controlling Confounding Effect of Irrelevant Sentences Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we show that factual inconsistency can be caused by irrelevant parts of the input text, which act as confounders. |
ASISH GHOSHAL et. al. | arxiv-cs.CL | 2022-12-19 |
333 | Graph-based Semantical Extractive Text Analysis Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. |
Mina Samizadeh; | arxiv-cs.CL | 2022-12-19 |
334 | Inverse Reinforcement Learning for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce inverse reinforcement learning (IRL) as an effective paradigm for training abstractive summarization models, imitating human summarization behaviors. |
Yu Fu; Deyi Xiong; Yue Dong; | arxiv-cs.CL | 2022-12-19 |
335 | Improving The Robustness of Summarization Models By Detecting and Removing Input Noise Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a large empirical study quantifying the sometimes severe loss in performance (up to 12 ROUGE-1 points) from different types of input noise for a range of datasets and model sizes. |
KUNDAN KRISHNA et. al. | arxiv-cs.CL | 2022-12-19 |
336 | What to Read in A Contract? Party-Specific Summarization of Legal Obligations, Entitlements, and Prohibitions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new task of party-specific extractive summarization for legal contracts to facilitate faster reviewing and improved comprehension of rights and duties. |
Abhilasha Sancheti; Aparna Garimella; Balaji Vasan Srinivasan; Rachel Rudinger; | arxiv-cs.CL | 2022-12-19 |
337 | Difformer: Empowering Diffusion Models on The Embedding Space for Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In addition, we find the normal level of noise causes insufficient training of the model. To address the above challenges, we propose Difformer, an embedding diffusion model based on Transformer, which consists of three essential modules including an additional anchor loss function, a layer normalization module for embeddings, and a noise factor to the Gaussian noise. |
ZHUJIN GAO et. al. | arxiv-cs.CL | 2022-12-19 |
338 | Advancing Multilingual Pre-training: TRIP Triangular Document-level Pre-training for Multilingual Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite the success of multilingual sequence-to-sequence pre-training, most existing approaches rely on document-level monolingual corpora in many different languages, sentence-level bilingual corpora,\footnote{In this paper, we use `bilingual corpora’ to denote parallel corpora with `bilingual translation pairs’ in many different language pairs, each consisting of two sentences/documents with the same meaning written in different languages. |
HONGYUAN LU et. al. | arxiv-cs.CL | 2022-12-15 |
339 | TRIP: Triangular Document-level Pre-training for Multilingual Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Despite the success of multilingual sequence-to-sequence pre-training, most existing approaches rely on document-level monolingual corpora in many different languages, … |
HONGYUAN LU et. al. | ArXiv | 2022-12-15 |
340 | Meeting Summarization: A Survey of The State of The Art Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this survey, we aim to cover recent meeting summarization techniques. |
Lakshmi Prasanna Kumar; Arman Kabiri; | arxiv-cs.CL | 2022-12-15 |
341 | Searching for Effective Multilingual Fine-Tuning Methods: A Case Study in Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we perform an extensive empirical evaluation of various tuning strategies for multilingual learning, particularly in the context of text summarization. |
Yiwei Qin; Graham Neubig; Pengfei Liu; | arxiv-cs.CL | 2022-12-12 |
342 | Implementing Deep Learning-Based Approaches for Article Summarization in Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a summary of various deep-learning approaches used for the ILSUM 2022 Indic language summarization datasets. |
Rahul Tangsali; Aabha Pingle; Aditya Vyawahare; Isha Joshi; Raviraj Joshi; | arxiv-cs.CL | 2022-12-11 |
343 | RoSummary: Control Tokens for Romanian News Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Significant progress has been achieved in text generation due to recent developments in neural architectures; nevertheless, this task remains challenging, especially for … |
Mihai Alexandru Niculescu; Stefan Ruseti; M. Dascalu; | Algorithms | 2022-12-11 |
344 | FIRE 2022 ILSUM Track: Indian Language Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This abstract provides a short overview of the first edition of the shared task on Indian Language Summarization (ILSUM) organized at the 14th Forum for Information Retrieval … |
Shrey Satapara; Bhavan Modha; Sandip J Modha; Parth Mehta; | Proceedings of the 14th Annual Meeting of the Forum for … | 2022-12-09 |
345 | Auto-regressive Extractive Summarization with Replacement Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tianyu Zhu; Wen Hua; Jianfeng Qu; S. Hosseini; Xiaofang Zhou; | World Wide Web | 2022-12-09 |
346 | KATSum: Knowledge-aware Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel model, named as Knowledge-aware Abstractive Text Summarization, which leverages the advantages offered by Knowledge Graph to enhance the standard Seq2Seq model. |
Guan Wang; Weihua Li; Edmund Lai; Jianhua Jiang; | arxiv-cs.CL | 2022-12-06 |
347 | Document-Level Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our work addresses the problem of document-level summarization by studying how efficient Transformer techniques can be used to improve the automatic summarization of very long texts. |
Gonçalo Raposo; Afonso Raposo; Ana Sofia Carmo; | arxiv-cs.CL | 2022-12-06 |
348 | Improved Beam Search for Hallucination Mitigation in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the use of the Natural Language Inference (NLI) entailment metric to detect and prevent hallucinations in summary generation. |
Arvind Krishna Sridhar; Erik Visser; | arxiv-cs.CL | 2022-12-05 |
349 | Text Summarization Using Transformer Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The increased availability of online feedback or review tools, and the enormous amount of information on these platforms, have made text summarization a vital research area in … |
Jaishree Ranganathan; Gloria Abuka; | 2022 Ninth International Conference on Social Networks … | 2022-11-29 |
350 | Prompted Opinion Summarization with GPT-3.5 IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Large language models have shown impressive performance across a wide variety of tasks, including text summarization. In this paper, we show that this strong performance extends to opinion summarization. |
Adithya Bhaskar; Alexander R. Fabbri; Greg Durrett; | arxiv-cs.CL | 2022-11-28 |
351 | Best-$k$ Search Algorithm for Neural Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a deterministic search algorithm balancing both quality and diversity. |
Jiacheng Xu; Caiming Xiong; Silvio Savarese; Yingbo Zhou; | arxiv-cs.CL | 2022-11-21 |
352 | GoSum: Extractive Summarization of Long Documents By Reinforcement Learning and Graph Organized Discourse State Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization. |
Junyi Bian; Xiaodi Huang; Hong Zhou; Shanfeng Zhu; | arxiv-cs.CL | 2022-11-18 |
353 | ED-FAITH: Evaluating Dialogue Summarization on Faithfulness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluate common faithfulness metrics on dialogue datasets and observe that most metrics correlate poorly with human judgements despite performing well on news datasets. |
Sicong Huang; Asli Celikyilmaz; Haoran Li; | arxiv-cs.CL | 2022-11-15 |
354 | Structured Abstract Summarization of Scientific Articles: Summarization Using Full‐text Section Information Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The automatic summarization of scientific articles differs from other text genres because of the structured format and longer text length. Previous approaches have focused on … |
Hanseok Oh; Seojin Nam; Yongjun Zhu; | Journal of the Association for Information Science and … | 2022-11-14 |
355 | CREATIVESUMM: Shared Task on Automatic Summarization for Creative Writing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces the shared task of summarizing documents in several creative domains, namely literary texts, movie scripts, and television scripts. |
DIVYANSH AGARWAL et. al. | arxiv-cs.CL | 2022-11-10 |
356 | NLP Tool for Extracting Relevant Information from Criminal Reports or Fakes/Propaganda Content Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The goal of paper is to develop a natural language processing system to extract relevant information from criminal reports or fake/propaganda. A detailed description of the … |
V. VYSOTSKA et. al. | 2022 IEEE 17th International Conference on Computer … | 2022-11-10 |
357 | Novel Chapter Abstractive Summarization Using Spinal Tree Aware Sub-Sentential Content Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a pipelined extractive-abstractive approach where the extractive step filters the content that is passed to the abstractive component. |
HARDY HARDY et. al. | arxiv-cs.CL | 2022-11-09 |
358 | Unsupervised Extractive Summarization with Heterogeneous Graph Embeddings for Chinese Document Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we are the first to propose an unsupervised extractive summarizaiton method with heterogeneous graph embeddings (HGEs) for Chinese document. |
Chen Lin; Ye Liu; Siyu An; Di Yin; | arxiv-cs.CL | 2022-11-09 |
359 | Computing and Exploiting Document Structure to Improve Unsupervised Extractive Summarization of Legal Case Decisions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an unsupervised graph-based ranking model that uses a reweighting algorithm to exploit properties of the document structure of legal case decisions. |
Yang Zhong; Diane Litman; | arxiv-cs.CL | 2022-11-06 |
360 | Submodular Maximization in Clean Linear Time Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we provide the first deterministic algorithm that achieves $1/2$-approximation for submodular maximization subject to a knapsack constraint, while making a number of queries that scales only linearly with the size of the ground set $n$. |
Wenxin Li; Moran Feldman; Ehsan Kazemi; Amin Karbasi; | nips | 2022-11-06 |
361 | Multi-LexSum: Real-world Summaries of Civil Rights Lawsuits at Multiple Granularities IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Multi-LexSum is a multi-doc summarization dataset for civil rights litigations lawsuits with summaries of three granularities. |
ZEJIANG SHEN et. al. | nips | 2022-11-06 |
362 | Towards Improving Faithfulness in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a Faithfulness Enhanced Summarization model (FES), which is designed for addressing these two problems and improving faithfulness in abstractive summarization. |
Xiuying Chen; Mingzhe Li; Xin Gao; Xiangliang Zhang; | nips | 2022-11-06 |
363 | Latent Prompt Tuning for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Lotus (shorthand for Latent Prompt Tuning for Summarization), which is a single model that can be applied in both controlled and uncontrolled (without control signals) modes. |
Yubo Zhang; Xingxing Zhang; Xun Wang; Si-qing Chen; Furu Wei; | arxiv-cs.CL | 2022-11-03 |
364 | FRSUM: Towards Faithful Abstractive Summarization Via Enhancing Factual Robustness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the faithfulness of existing systems from a new perspective of factual robustness which is the ability to correctly generate factual information over adversarial unfaithful information. |
WENHAO WU et. al. | arxiv-cs.CL | 2022-11-01 |
365 | Questioning The Validity of Summarization Datasets and Improving Their Factual Consistency Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Due to this lack of well-defined formulation, a large number of popular abstractive summarization datasets are constructed in a manner that neither guarantees validity nor meets one of the most essential criteria of summarization: factual consistency. In this paper, we address this issue by combining state-of-the-art factual consistency models to identify the problematic instances present in popular summarization datasets. |
Yanzhu Guo; Chloé Clavel; Moussa Kamal Eddine; Michalis Vazirgiannis; | arxiv-cs.CL | 2022-10-31 |
366 | CCS Explorer: Relevance Prediction, Extractive Summarization, and Named Entity Recognition from Clinical Cohort Studies Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose CCS Explorer, an end-to-end system for relevance prediction of sentences, extractive summarization, and patient, outcome, and intervention entity detection from CCS. |
Irfan Al-Hussaini; Davi Nakajima An; Albert J. Lee; Sarah Bi; Cassie S. Mitchell; | arxiv-cs.CL | 2022-10-31 |
367 | A Preliminary Exploration of Extractive Multi-Document Summarization in Hyperbolic Space Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the above structural property is hard to model in the Euclidean space. Inspired by the above issues, we explore extractive summarization in the hyperbolic space and propose a new Hyperbolic Siamese Network for the matching-based extractive summarization (HyperSiameseNet). |
Mingyang Song; Yi Feng; Liping Jing; | cikm | 2022-10-29 |
368 | Faithful Abstractive Summarization Via Fact-aware Consistency-constrained Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this way, the summarization results could be vulnerable to hallucinations, i.e., the semantic-level inconsistency between a summary and corresponding original document. To deal with this challenge, in this paper, we propose a novel fact-aware abstractive summarization model, named Entity-Relation Pointer Generator Network (ERPGN). |
Yuanjie Lyu; Chen Zhu; Tong Xu; Zikai Yin; Enhong Chen; | cikm | 2022-10-29 |
369 | Improving Abstractive Summarization with Energy-based Re-ranking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we intend to close the loop by leveraging the recent advances in summarization metrics to create quality-aware abstractive summarizers. Namely, we propose an energy-based model that learns to re-rank summaries according to one or a combination of these metrics. |
Diogo Pernes; Afonso Mendes; André F. T. Martins; | arxiv-cs.CL | 2022-10-27 |
370 | Analyzing Multi-Task Learning for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We group tasks into one of three strategies, i.e., sequential, simultaneous, and continual multi-task learning, and evaluate trained models through two downstream tasks. |
Frederic Kirstein; Jan Philip Wahle; Terry Ruas; Bela Gipp; | arxiv-cs.CL | 2022-10-26 |
371 | CrisisLTLSum: A Benchmark for Local Crisis Event Timeline Extraction and Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents CrisisLTLSum, the largest dataset of local crisis event timelines available to date. |
HOSSEIN RAJABY FAGHIHI et. al. | arxiv-cs.CL | 2022-10-25 |
372 | LANS: Large-scale Arabic News Summarization Corpus Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We build, LANS, a large-scale and diverse dataset for Arabic Text Summarization task. |
Abdulaziz Alhamadani; Xuchao Zhang; Jianfeng He; Chang-Tien Lu; | arxiv-cs.CL | 2022-10-24 |
373 | Correcting Diverse Factual Errors in Abstractive Summarization Via Post-Editing and Language Model Infilling IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to generate hard, representative synthetic examples of non-factual summaries through infilling language models. |
Vidhisha Balachandran; Hannaneh Hajishirzi; William W. Cohen; Yulia Tsvetkov; | arxiv-cs.CL | 2022-10-22 |
374 | Extractive Summarization of Legal Decisions Using Multi-task Learning and Maximal Marginal Relevance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents techniques for extractive summarization of legal decisions in a low-resource setting using limited expert annotated data. |
Abhishek Agarwal; Shanshan Xu; Matthias Grabmair; | arxiv-cs.CL | 2022-10-22 |
375 | Summary Workbench: Unifying Application and Evaluation of Text Summarization Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents Summary Workbench, a new tool for developing and evaluating text summarization models. |
Shahbaz Syed; Dominik Schwabe; Martin Potthast; | arxiv-cs.CL | 2022-10-18 |
376 | Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This survey provides a comprehensive investigation on existing work for abstractive dialogue summarization from scenarios, approaches to evaluations. |
Qi Jia; Yizhu Liu; Siyu Ren; Kenny Q. Zhu; | arxiv-cs.CL | 2022-10-18 |
377 | Towards Summary Candidates Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recently, re-ranking methods have been proposed, to learn to select a better summary candidate. |
Mathieu Ravaut; Shafiq Joty; Nancy F. Chen; | arxiv-cs.CL | 2022-10-17 |
378 | Social Biases in Automatic Evaluation Metrics for NLG Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the paper, we propose an evaluation method based on Word Embeddings Association Test (WEAT) and Sentence Embeddings Association Test (SEAT) to quantify social biases in evaluation metrics and discover that social biases are also widely present in some model-based automatic evaluation metrics. |
Mingqi Gao; Xiaojun Wan; | arxiv-cs.CL | 2022-10-17 |
379 | Legal Case Document Summarization: Extractive and Abstractive Methods and Their Evaluation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we carry out extensive experiments with several extractive and abstractive summarization methods (both supervised and unsupervised) over three legal summarization datasets that we have developed. |
ABHAY SHUKLA et. al. | arxiv-cs.CL | 2022-10-14 |
380 | Shortcomings of Question Answering Based Factuality Frameworks for Error Localization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: These have been shown to work well at predicting summary-level factuality and have potential to localize errors within summaries, but this latter capability has not been systematically evaluated in past research. In this paper, we conduct the first such analysis and find that, contrary to our expectations, QA-based frameworks fail to correctly identify error spans in generated summaries and are outperformed by trivial exact match baselines. |
Ryo Kamoi; Tanya Goyal; Greg Durrett; | arxiv-cs.CL | 2022-10-13 |
381 | Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based Methods Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In both automatic and human evaluation setups, using token-level attributions from text classification tasks, we compare two novel methods (search-based and instruction-based verbalizations) against conventional feature importance representations (heatmap visualizations and extractive rationales), measuring simulatability, faithfulness, helpfulness and ease of understanding. |
NILS FELDHUS et. al. | arxiv-cs.CL | 2022-10-13 |
382 | Improving Graph-Based Text Representations with Character and Word Level N-grams Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Graph-based text representation focuses on how text documents are represented as graphs for exploiting dependency information between tokens and documents within a corpus. |
Wenzhe Li; Nikolaos Aletras; | arxiv-cs.CL | 2022-10-12 |
383 | Readability Controllable Biomedical Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing biomedical document summarization systems have paid little attention to readability control, leaving users with summaries that are incompatible with their levels of expertise. In recognition of this urgent demand, we introduce a new task of readability controllable summarization for biomedical documents, which aims to recognise users’ readability demands and generate summaries that better suit their needs: technical summaries for experts and plain language summaries (PLS) for laymen. |
Zheheng Luo; Qianqian Xie; Sophia Ananiadou; | arxiv-cs.CL | 2022-10-10 |
384 | Hierarchical3D Adapters for Long Video-to-text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on video-to-text summarization and investigate how to best utilize multimodal information for summarizing long inputs (e.g., an hour-long TV show) into long outputs (e.g., a multi-sentence summary). |
Pinelopi Papalampidi; Mirella Lapata; | arxiv-cs.CL | 2022-10-10 |
385 | Unsupervised Summarization of Privacy Concerns in Mobile Application Reviews Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The proliferation of mobile applications (app) over the past decade has imposed unprecedented challenges on end-users privacy. Apps constantly demand access to sensitive user … |
Fahimeh Ebrahimi; Anas Mahmoud; | Proceedings of the 37th IEEE/ACM International Conference … | 2022-10-10 |
386 | EDU-level Extractive Summarization with Varying Summary Lengths Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: EDU-VL learns to encode and predict probabilities of EDUs in the document, generate multiple candidate summaries with varying lengths based on various $k$ values, and encode and score candidate summaries, in an end-to-end training manner. |
YUPING WU et. al. | arxiv-cs.CL | 2022-10-08 |
387 | Just ClozE! A Novel Framework for Evaluating The Factual Consistency Faster in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a cloze-based evaluation framework called ClozE and show the great potential of the cloze-based metric. |
YIYANG LI et. al. | arxiv-cs.CL | 2022-10-06 |
388 | Extractive Text Summarization Using Clustering-based Topic Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View |
R. Belwal; Sawan Rai; Atul Gupta; | Soft Computing | 2022-10-04 |
389 | Probing of Quantitative Values in Abstractive Summarization Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a set of probing tests to evaluate the efficacy of abstract summarization models’ modeling of quantitative values found in the input text. |
Nathan M. White; | arxiv-cs.CL | 2022-10-02 |
390 | Calibrating Sequence Likelihood Improves Conditional Language Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce sequence likelihood calibration (SLiC) where the likelihood of model generated sequences are calibrated to better align with reference sequences in the model’s latent space. |
YAO ZHAO et. al. | arxiv-cs.CL | 2022-09-30 |
391 | Out-of-Distribution Detection and Selective Generation for Conditional Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, the space of potential low-quality outputs is larger as arbitrary text can be generated and it is important to know when to trust the generated output. We present a highly accurate and lightweight OOD detection method for CLMs, and demonstrate its effectiveness on abstractive summarization and translation. |
JIE REN et. al. | arxiv-cs.CL | 2022-09-30 |
392 | COLO: A Contrastive Learning Based Re-ranking Framework for One-Stage Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a Contrastive Learning based re-ranking framework for one-stage summarization called COLO. |
CHENXIN AN et. al. | arxiv-cs.CL | 2022-09-29 |
393 | WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from Paragraphs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce WikiDes, a novel dataset to generate short descriptions of Wikipedia articles for the problem of text summarization. |
HOANG THANG TA et. al. | arxiv-cs.CL | 2022-09-26 |
394 | News Summarization and Evaluation in The Era of GPT-3 IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The recent success of prompting large language models like GPT-3 has led to a paradigm shift in NLP research. In this paper, we study its impact on text summarization, focusing on the classic benchmark domain of news summarization. |
Tanya Goyal; Junyi Jessy Li; Greg Durrett; | arxiv-cs.CL | 2022-09-25 |
395 | Controllable Text Generation for Open-Domain Creativity and Fairness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, I introduce our recent works on controllable text generation to enhance the creativity and fairness of language generation models. |
Nanyun Peng; | arxiv-cs.CL | 2022-09-24 |
396 | Summarization Programs: Interpretable Abstractive Summarization with Neural Modular Trees IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose the Summarization Program (SP), an interpretable modular framework consisting of an (ordered) list of binary trees, each encoding the step-by-step generative process of an abstractive summary sentence from the source document. |
Swarnadeep Saha; Shiyue Zhang; Peter Hase; Mohit Bansal; | arxiv-cs.CL | 2022-09-21 |
397 | Adapting Pretrained Text-to-Text Models for Long Text Sequences IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present an empirical study of adapting an existing pretrained text-to-text model for long-sequence inputs. |
Wenhan Xiong; Anchit Gupta; Shubham Toshniwal; Yashar Mehdad; Wen-tau Yih; | arxiv-cs.CL | 2022-09-20 |
398 | Exploring Optimal Granularity for Extractive Summarization of Unstructured Health Records: Analysis of The Largest Multi-Institutional Archive of Health Records in Japan Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We defined clinical segments in this study, aiming to express the smallest medically meaningful concepts. |
Kenichiro Ando; Takashi Okumura; Mamoru Komachi; Hiromasa Horiguchi; Yuji Matsumoto; | arxiv-cs.CL | 2022-09-20 |
399 | Selective Token Generation for Few-shot Natural Language Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, this added adapter is still easy to disregard the knowledge of the PLM especially for few-shot natural language generation (NLG) since an entire sequence is usually generated by only the newly trained adapter. Therefore, in this work, we develop a novel additive learning algorithm based on reinforcement learning (RL) that selectively outputs language tokens between the task-general PLM and the task-specific adapter during both training and inference. |
Daejin Jo; Taehwan Kwon; Eun-Sol Kim; Sungwoong Kim; | arxiv-cs.CL | 2022-09-16 |
400 | Harnessing Abstractive Summarization for Fact-Checked Claim Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a new workflow for efficiently detecting previously fact-checked claims that uses abstractive summarization to generate crisp queries. |
Varad Bhatnagar; Diptesh Kanojia; Kameswari Chebrolu; | arxiv-cs.CL | 2022-09-10 |
401 | Applying Transformer-based Text Summarization for Keyphrase Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we experiment with popular transformer-based models for abstractive text summarization using four benchmark datasets for keyphrase extraction. |
Anna Glazkova; Dmitry Morozov; | arxiv-cs.CL | 2022-09-08 |
402 | Entity-based SpanCopy for Abstractive Summarization to Improve The Factual Consistency Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on entity-level factual inconsistency, i.e. reducing the mismatched entities between the generated summaries and the source documents. |
Wen Xiao; Giuseppe Carenini; | arxiv-cs.CL | 2022-09-07 |
403 | Comparing Methods for Extractive Summarization of Call Centre Dialogue Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper provides results of evaluating some text summarisation techniques for the purpose of producing call summaries for contact centre solutions. We specifically focus on extractive summarisation methods, as they do not require any labelled data and are fairly quick and easy to implement for production use. |
Alexandra N. Uma; Dmitry Sityaev; | arxiv-cs.CL | 2022-09-06 |
404 | ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a simple technique to capture the argumentative structure of legal documents by integrating argument role labeling into the summarization process. |
Mohamed Elaraby; Diane Litman; | arxiv-cs.CL | 2022-09-04 |
405 | Enhancing Semantic Understanding with Self-supervised Methods for Abstractive Dialogue Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce self-supervised methods to compensate shortcomings to train a dialogue summarization model. |
Hyunjae Lee; Jaewoong Yun; Hyunjin Choi; Seongho Joe; Youngjune L. Gwon; | arxiv-cs.CL | 2022-09-01 |
406 | A Systematic Literature Review of Keyphrases Extraction Approaches Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The keyphrases of a document are the textual units that characterize its content such as the topics it addresses, its ideas, their field, etc. Thousands of books, articles and web … |
Lahbib Ajallouda; F. Z. Fagroud; A. Zellou; E. Benlahmar; | Int. J. Interact. Mob. Technol. | 2022-08-31 |
407 | To Adapt or to Fine-tune: A Case Study on Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we carry out multifaceted investigations on fine-tuning and adapters for summarization tasks with varying complexity: language, domain, and task transfer. |
Zheng Zhao; Pinzhen Chen; | arxiv-cs.CL | 2022-08-30 |
408 | GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel model, the graph contrastive topic enhanced language model (GRETEL), that incorporates the graph contrastive topic model with the pre-trained language model, to fully leverage both the global and local contextual semantics for long document extractive summarization. |
Qianqian Xie; Jimin Huang; Tulika Saha; Sophia Ananiadou; | arxiv-cs.CL | 2022-08-21 |
409 | DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: —Transformer is a deep learning language model widely used for natural language processing (NLP) services in datacenters. Among transformer models, Generative Pre- trained … |
SEONGMIN HONG et. al. | 2022 IEEE Hot Chips 34 Symposium (HCS) | 2022-08-21 |
410 | Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents Z-Code++, a new pre-trained language model optimized for abstractive text summarization. |
PENGCHENG HE et. al. | arxiv-cs.CL | 2022-08-20 |
411 | Automatic Text Summarization of Biomedical Text Data: A Systematic Review IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, the evolution of technology has led to an increase in text data obtained from many sources. In the biomedical domain, text information has also evidenced this … |
Andrea Chaves; C. Kesiku; B. Garcia-Zapirain; | Inf. | 2022-08-19 |
412 | Sparse Optimization for Unsupervised Extractive Summarization of Long Documents with The Frank-Wolfe Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We address the problem of unsupervised extractive document summarization, especially for long documents. |
Alicia Y. Tsai; Laurent El Ghaoui; | arxiv-cs.CL | 2022-08-19 |
413 | Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a text editor to help users plan, structure and reflect on their writing process. |
Hai Dang; Karim Benharrak; Florian Lehmann; Daniel Buschek; | arxiv-cs.HC | 2022-08-19 |
414 | Extractive Summarization Using Concept‐space and Keyword Phrase Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is widely used to extract relevant information from documents. The extensive unstructured data are generated in various domains, developing a concise and … |
Parminder Pal Singh Bedi; M. Bala; K. Sharma; | Expert Systems | 2022-08-10 |
415 | Template-based Abstractive Microblog Opinion Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We introduce the task of microblog opinion summarization (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain. The dataset … |
IMAN MUNIRE BILAL et. al. | Transactions of the Association for Computational … | 2022-08-08 |
416 | Abstractive Meeting Summarization: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we provide an overview of the challenges raised by the task of abstractive meeting summarization and of the data sets, models and evaluation metrics that have been used to tackle the problems. |
Virgile Rennard; Guokan Shang; Julie Hunter; Michalis Vazirgiannis; | arxiv-cs.CL | 2022-08-08 |
417 | DeepSumm: Exploiting Topic Models and Sequence to Sequence Networks for Extractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Akanksha Joshi; Eduardo Fidalgo; Enrique Alegre; Laura Fernández-Robles; | Expert Syst. Appl. | 2022-08-01 |
418 | A Data-driven Latent Semantic Analysis for Automatic Text Summarization Using LDA Topic Modelling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, PyLDAvis web-based interactive visualization tool was used to visualise the selected topics. |
Daniel F. O. Onah; Elaine L. L. Pang; Mahmoud El-Haj; | arxiv-cs.IR | 2022-07-23 |
419 | An Overview of Distant Supervision for Relation Extraction with A Focus on Denoising and Pre-training Methods Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Relation Extraction (RE) is a foundational task of natural language processing. RE seeks to transform raw, unstructured text into structured knowledge by identifying relational … |
William Hogan; | arxiv-cs.CL | 2022-07-17 |
420 | Controlling Conditional Language Models Without Catastrophic Forgetting IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we extend DPG to conditional tasks by proposing Conditional DPG (CDPG). |
Tomasz Korbak; Hady Elsahar; German Kruszewski; Marc Dymetman; | icml | 2022-07-15 |
421 | Forming Trees with Treeformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Treeformer, a general-purpose encoder module inspired by the CKY algorithm which learns a composition operator and pooling function to construct hierarchical encodings for phrases and sentences. |
Nilay Patel; Jeffrey Flanigan; | arxiv-cs.CL | 2022-07-14 |
422 | MuchSUM: Multi-channel Graph Neural Network for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents MuchSUM, a better approach for extractive text summarization. |
QIANREN MAO et. al. | sigir | 2022-07-12 |
423 | On Extractive Summarization for Profile-centric Neural Expert Search in Academia Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite offering a complete picture of each candidate’s scientific output, such lengthy profiles make it inefficient to leverage state-of-the-art neural architectures for inferring expertise. To overcome this limitation, we investigate the suitability of extractive summarization as a mechanism to reduce candidate profiles for semantic encoding using Transformers. |
Rennan C. Lima; Rodrygo L. T. Santos; | sigir | 2022-07-12 |
424 | What Makes A Good Podcast Summary? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Using a collection of podcast summaries produced by different algorithms alongside human judgments of summary quality obtained from the TREC 2020 Podcasts Track, we study the correlations between various automatic evaluation metrics and human judgments, as well as the linguistic aspects of summaries that result in strong evaluations. |
Rezvaneh Rezapour; Sravana Reddy; Rosie Jones; Ian Soboroff; | sigir | 2022-07-12 |
425 | A General Contextualized Rewriting Framework for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate contextualized rewriting, which consumes the entire document and considers the summary context. |
Guangsheng Bao; Yue Zhang; | arxiv-cs.CL | 2022-07-12 |
426 | Extractive Elementary Discourse Units for Improving Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we apply elementary discourse unit (EDU) as textual unit of content selection. |
Ye Xiong; Teeradaj Racharak; Minh Le Nguyen; | sigir | 2022-07-12 |
427 | Summarizing Legal Regulatory Documents Using Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper aims at applying advanced extractive summarization to democratize the understanding of regulations, so that non-jurists can decide which regulations deserve further follow-up. |
SVEA KLAUS et. al. | sigir | 2022-07-12 |
428 | Lightweight Meta-Learning for Low-Resource Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Furthermore, the need for low-resource abstractive summarization task is emerging but existing methods for the task such as transfer learning still have domain shifting and overfitting problems. To address these problems, we propose a new framework for low-resource abstractive summarization using a meta-learning algorithm that can quickly adapt to a new domain using small data. |
Taehun Huh; Youngjoong Ko; | sigir | 2022-07-12 |
429 | SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the existing evaluation metrics for summary text are only rough proxies for summary quality, suffering from low correlation with human scoring and inhibition of summary diversity. To solve these problems, we propose SummScore, a comprehensive metric for summary quality evaluation based on CrossEncoder. |
WUHANG LIN et. al. | arxiv-cs.CL | 2022-07-11 |
430 | DACSA: A Large-scale Dataset for Automatic Summarization of Catalan and Spanish Newspaper Articles Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we describe the construction of a corpus of Catalan and Spanish newspapers, the Dataset for Automatic summarization of Catalan and Spanish newspaper Articles (DACSA) corpus. |
Encarnaci?n Segarra Soriano; Vicent Ahuir; Llu?s-F. Hurtado; Jos? Gonz?lez; | naacl | 2022-07-09 |
431 | An Exploration of Post-Editing Effectiveness in Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, we explored whether post-editing offers advantages in text summarization. |
VIVIAN LAI et. al. | naacl | 2022-07-09 |
432 | FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present FactPEGASUS, an abstractive summarization model that addresses the problem of factuality during pre-training and fine-tuning: (1) We augment the sentence selection strategy of PEGASUS’s (Zhang et al., 2019) pre-training objective to create pseudo-summaries that are both important and factual; (2) We introduce three complementary components for fine-tuning. |
David Wan; Mohit Bansal; | naacl | 2022-07-09 |
433 | QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we conduct an extensive comparison of entailment and QA-based metrics, demonstrating that carefully choosing the components of a QA-based metric, especially question generation and answerability classification, is critical to performance. |
Alexander Fabbri; Chien-Sheng Wu; Wenhao Liu; Caiming Xiong; | naacl | 2022-07-09 |
434 | What Makes A Good and Useful Summary? Incorporating Users in Automatic Summarization Research Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we focus on university students, who make extensive use of summaries during their studies. |
Maartje Ter Hoeve; Julia Kiseleva; Maarten Rijke; | naacl | 2022-07-09 |
435 | Mapping The Design Space of Human-AI Interaction in Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We first conducted a systematic literature review of 70 papers, developing a taxonomy of five interactions in AI-assisted text generation and relevant design dimensions. We designed text summarization prototypes for each interaction. |
Ruijia Cheng; Alison Smith-Renner; Ke Zhang; Joel Tetreault; Alejandro Jaimes-Larrarte; | naacl | 2022-07-09 |
436 | From Spoken Dialogue to Formal Summary: An Utterance Rewriting for Dialogue Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the current state-of-the-art models pay more attention on the topic or structure of summary, rather than the consistency of dialogue summary with its input dialogue context, which may suffer from the personal and logical inconsistency problem. In this paper, we propose a new model, named ReWriteSum, to tackle this problem. |
YUE FANG et. al. | naacl | 2022-07-09 |
437 | Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, state-of-the-art NLI models perform poorly in this context due to their inability to generalize to the target task. In this work, we show that NLI models can be effective for this task when the training data is augmented with high-quality task-oriented examples. |
Prasetya Utama; Joshua Bambrick; Nafise Moosavi; Iryna Gurevych; | naacl | 2022-07-09 |
438 | FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent works have shown promising improvements in factuality error identification using text or dependency arc entailments; however, they do not consider the entire semantic graph simultaneously. To this end, we propose FactGraph, a method that decomposes the document and the summary into structured meaning representations (MR), which are more suitable for factuality evaluation. |
Leonardo Ribeiro; Mengwen Liu; Iryna Gurevych; Markus Dreyer; Mohit Bansal; | naacl | 2022-07-09 |
439 | Meta-Learning The Difference: Preparing Large Language Models for Efficient Adaptation Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Large pretrained language models (PLMs) are often domain- or task-adapted via fine-tuning or prompting. Finetuning requires modifying all of the parameters and having enough data … |
Zejiang Hou; Julian Salazar; George Polovets; | arxiv-cs.CL | 2022-07-07 |
440 | Improving The Faithfulness of Abstractive Summarization Via Entity Coverage Control IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a method to remedy entity-level extrinsic hallucinations with Entity Coverage Control (ECC). |
Haopeng Zhang; Semih Yavuz; Wojciech Kryscinski; Kazuma Hashimoto; Yingbo Zhou; | arxiv-cs.CL | 2022-07-05 |
441 | Multimodal Frame-Scoring Transformer for Video Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Second, existing datasets for generic video summarization are relatively insufficient to train a caption generator used for extracting text information from a video and to train the multimodal feature extractors. To address these two problems, this paper proposes the Multimodal Frame-Scoring Transformer (MFST), a framework exploiting visual, text, and audio features and scoring a video with respect to frames. |
Jeiyoon Park; Kiho Kwoun; Chanhee Lee; Heuiseok Lim; | arxiv-cs.LG | 2022-07-05 |
442 | Frequent Item-set Mining and Clustering Based Ranked Biomedical Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Supriya Gupta; Aakanksha Sharaff; N. K. Nagwani; | The Journal of Supercomputing | 2022-07-04 |
443 | An Empirical Survey on Long Document Summarization: Datasets, Models and Metrics IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recently, with the advent of neural architectures, significant research efforts have been made to advance automatic text summarization systems, and numerous studies on the challenges of extending these systems to the long document domain have emerged. In this survey, we provide a comprehensive overview of the research on long document summarization and a systematic evaluation across the three principal components of its research setting: benchmark datasets, summarization models, and evaluation metrics. |
Huan Yee Koh; Jiaxin Ju; Ming Liu; Shirui Pan; | arxiv-cs.CL | 2022-07-02 |
444 | Controllable Text Generation for Open-Domain Creativity and Fairness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, I introduce our recent works on controllable text generation to enhance the creativity and fairness of language generation models. |
Nanyun (Violet) Peng; | ijcai | 2022-07-01 |
445 | Pre-trained Language Models with Domain Knowledge for Biomedical Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View |
Qianqian Xie; Jennifer A Bishop; P. Tiwari; S. Ananiadou; | Knowl. Based Syst. | 2022-07-01 |
446 | Mapping The Design Space of Human-AI Interaction in Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: From a human-centered perspective, we map the design opportunities and considerations for human-AI interaction in text summarization and broader text generation tasks. |
Ruijia Cheng; Alison Smith-Renner; Ke Zhang; Joel R. Tetreault; Alejandro Jaimes; | arxiv-cs.HC | 2022-06-29 |
447 | GATSum: Graph-Based Topic-Aware Abstract Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The purpose of text summarization is to compress a text document into a summary containing key information. abstract approaches are challenging tasks, it is necessary to design a … |
Ming Jiang; Yifan Zou; Jian Xu; Min Zhang; | Inf. Technol. Control. | 2022-06-23 |
448 | Anaphora Resolved Abstractive Text Summarization (AR-ATS) System Related Papers Related Patents Related Grants Related Venues Related Experts View |
N. Moratanch; S. Chitrakala; | Multimedia Tools and Applications | 2022-06-18 |
449 | An Extractive-and-Abstractive Framework for Source Code Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To generate human-written-like summaries with preserved factual details, we propose a novel extractive-and-abstractive framework. |
WEISONG SUN et. al. | arxiv-cs.SE | 2022-06-14 |
450 | Indian Legal Text Summarization: A Text Normalization-based Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the Indian court system, pending cases have long been a problem. There are more than 4 crore cases outstanding. Manually summarising hundreds of documents is a time-consuming … |
Satyajit Ghosh; Mousumi Dutta; Tanaya Das; | 2022 IEEE 19th India Council International Conference … | 2022-06-13 |
451 | An Exploration of Post-Editing Effectiveness in Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In similar text generation tasks (e.g., machine translation), human-AI collaboration in the form of post-editing AI-generated text reduces human workload and improves the quality of AI output. Therefore, we explored whether post-editing offers advantages in text summarization. |
VIVIAN LAI et. al. | arxiv-cs.CL | 2022-06-13 |
452 | Indian Legal Text Summarization: A Text Normalisation-based Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the Indian court system, pending cases have long been a problem. There are more than 4 crore cases outstanding. Manually summarising hundreds of documents is a time-consuming … |
Satyajit Ghosh; Mousumi Dutta; Tanaya Das; | arxiv-cs.CL | 2022-06-13 |
453 | CLTS+: A New Chinese Long Text Summarization Dataset with Abstractive Summaries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We analyze the extraction strategies used in CLTS+ summaries against other datasets to quantify the abstractiveness and difficulty of our new data and train several baselines on CLTS+ to verify the utility of it for improving the creative ability of models. |
Xiaojun Liu; Shunan Zang; Chuang Zhang; Xiaojun Chen; Yangyang Ding; | arxiv-cs.CL | 2022-06-08 |
454 | IntentVizor: Towards Generic Query Guided Interactive Video Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: First, the text query might not be enough to describe the exact and diverse needs of the user. Second, the user cannot edit once the summaries are produced, while we assume the needs of the user should be subtle and need to be adjusted interactively. To solve these two problems, we propose IntentVizor, an interactive video summarization framework guided by generic multi-modality queries. |
Guande Wu; Jianzhe Lin; Claudio T. Silva; | cvpr | 2022-06-07 |
455 | Findings of The The RuATD Shared Task 2022 on Artificial Text Detection in Russian IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present the shared task on artificial text detection in Russian, which is organized as a part of the Dialogue Evaluation initiative, held in 2022. |
TATIANA SHAMARDINA et. al. | arxiv-cs.CL | 2022-06-03 |
456 | Risks and Benefits of AI-generated Text Summarization for Expert Level Content in Graduate Health Informatics Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: AI-generated text summarization (AI-GTS) is now a popular topic in applied computer science education. It has proven helpful in various sectors, but its benefits and risks in … |
R. Merine; S. Purkayastha; | 2022 IEEE 10th International Conference on Healthcare … | 2022-06-01 |
457 | Graph-Based Text Summarization and Its Application on COVID-19 Twitter Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large volumes of structured and semi-structured data are being generated every day. Processing this large amount of data and extracting important information is a challenging … |
A. K. Das; Bhaavanaa Thumu; Apurba Sarkar; S. Vimal; A. Das; | Int. J. Uncertain. Fuzziness Knowl. Based Syst. | 2022-06-01 |
458 | Automatic Evaluation of Summary on Fidelity, Conciseness and Coherence for Text Summarization Based on Semantic Link Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mengyun Cao; H. Zhuge; | Expert Syst. Appl. | 2022-06-01 |
459 | NEWTS: A Corpus for News Topic-Focused Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces the first topical summarization corpus NEWTS, based on the well-known CNN/Dailymail dataset, and annotated via online crowd-sourcing. |
Seyed Ali Bahrainian; Sheridan Feucht; Carsten Eickhoff; | arxiv-cs.CL | 2022-05-31 |
460 | X-SCITLDR: Cross-Lingual Extreme Summarization of Scholarly Documents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we fill this research gap and present an abstractive cross-lingual summarization dataset for four different languages in the scholarly domain, which enables us to train and evaluate models that process English papers and generate summaries in German, Italian, Chinese and Japanese. |
Sotaro Takeshita; Tommaso Green; Niklas Friedrich; Kai Eckert; Simone Paolo Ponzetto; | arxiv-cs.CL | 2022-05-30 |
461 | CoNT: Contrastive Neural Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we analyse the underlying reasons and propose a new Contrastive Neural Text generation framework, CoNT. |
CHENXIN AN et. al. | arxiv-cs.CL | 2022-05-29 |
462 | Learning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a Non-Autoregressive Unsupervised Summarization (NAUS) approach, which does not require parallel data for training. |
Puyuan Liu; Chenyang Huang; Lili Mou; | arxiv-cs.CL | 2022-05-28 |
463 | Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the ever-evolving nature of summarization systems, metrics, and annotated benchmarks makes factuality evaluation a moving target, and drawing clear comparisons among metrics has become increasingly difficult. In this work, we aggregate factuality error annotations from nine existing datasets and stratify them according to the underlying summarization model. |
LIYAN TANG et. al. | arxiv-cs.CL | 2022-05-25 |
464 | Leveraging Locality in Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, the quadratic memory complexity of the self-attention module with respect to the input length hinders their applications in long text summarization. Instead of designing more efficient attention modules, we approach this problem by investigating if models with a restricted context can have competitive performance compared with the memory-efficient attention models that maintain a global context by treating the input as a single sequence. |
YIXIN LIU et. al. | arxiv-cs.CL | 2022-05-24 |
465 | Medical Scientific Table-to-Text Generation with Human-in-the-Loop Under The Data Sparsity Constraint Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, in practice, the problem is heavily impeded by the data paucity, data sparsity and inability of the state-of-the-art natural language generation models (including T5, PEGASUS and GPT-Neo) to produce accurate and reliable outputs. In this paper, we propose a novel table-to-text approach and tackle these problems with a novel two-step architecture which is enhanced by auto-correction, copy mechanism and synthetic data augmentation. |
HENG-YI WU et. al. | arxiv-cs.CL | 2022-05-24 |
466 | MaskEval: Weighted MLM-Based Evaluation for Text Summarization and Simplification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce MaskEval, a reference-less metric for text summarization and simplification that operates by performing masked language modeling (MLM) on the concatenation of the candidate and the source texts. |
Yu Lu Liu; Rachel Bawden; Thomas Scialom; Benoît Sagot; Jackie Chi Kit Cheung; | arxiv-cs.CL | 2022-05-24 |
467 | Counterfactual Data Augmentation Improves Factuality of Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a counterfactual data augmentation approach where we augment data with perturbed summaries that increase the training data diversity. |
Dheeraj Rajagopal; Siamak Shakeri; Cicero Nogueira dos Santos; Eduard Hovy; Chung-Ching Chang; | arxiv-cs.CL | 2022-05-24 |
468 | End-to-End Speech Summarization Using Restricted Self-Attention IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a single model optimized end-to-end for speech summarization. |
R. Sharma; S. Palaskar; A. W. Black; F. Metze; | icassp | 2022-05-22 |
469 | Integrating Multiple ASR Systems Into NLP Backend with Attention Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we reduce the impact of ASR errors on the NLP back-end by combining transcriptions from various ASR systems. |
T. Kano; A. Ogawa; M. Delcroix; S. Watanabe; | icassp | 2022-05-22 |
470 | TED Talk Teaser Generation with Pre-Trained Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we address the challenge of automatically generating teasers for TED talks. |
G. Vico; J. Niehues; | icassp | 2022-05-22 |
471 | On The Trade-off Between Redundancy and Local Coherence in Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we tackle the problem of summary redundancy in unsupervised extractive summarization of long, highly-redundant documents. |
Ronald Cardenas; Matthias Galle; Shay B. Cohen; | arxiv-cs.CL | 2022-05-20 |
472 | Lossless Acceleration for Seq2seq Generation with Aggressive Decoding IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Unlike the previous efforts (e.g., non-autoregressive decoding) speeding up seq2seq generation at the cost of quality loss, our approach aims to yield the identical (or better) generation compared with autoregressive decoding but in a significant speedup, achieved by innovative cooperation of aggressive decoding and verification that are both efficient due to parallel computing. |
Tao Ge; Heming Xia; Xin Sun; Si-Qing Chen; Furu Wei; | arxiv-cs.CL | 2022-05-20 |
473 | Evaluation of Transfer Learning for Polish with A Text-to-Text Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a new benchmark for assessing the quality of text-to-text models for Polish. |
ALEKSANDRA CHRABROWA et. al. | arxiv-cs.CL | 2022-05-18 |
474 | Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this way, it is possible to translate the English dataset to other languages and obtain different sets of labels again using heuristics. To fully leverage the information of these different sets of labels, we propose NLSSum (Neural Label Search for Summarization), which jointly learns hierarchical weights for these different sets of labels together with our summarization model. |
RUIPENG JIA et. al. | acl | 2022-05-17 |
475 | MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce MemSum (Multi-step Episodic Markov decision process extractive SUMmarizer), a reinforcement-learning-based extractive summarizer enriched at each step with information on the current extraction history. |
Nianlong Gu; Elliott Ash; Richard Hahnloser; | acl | 2022-05-17 |
476 | EntSUM: A Data Set for Entity-Centric Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose extensions to state-of-the-art summarization approaches that achieve substantially better results on our data set. |
Mounica Maddela; Mayank Kulkarni; Daniel Preotiuc-Pietro; | acl | 2022-05-17 |
477 | Faithful or Extractive? On Mitigating The Faithfulness-Abstractiveness Trade-off in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present a framework for evaluating the effective faithfulness of summarization systems, by generating a faithfulness-abstractiveness trade-off curve that serves as a control at different operating points on the abstractiveness spectrum. |
Faisal Ladhak; Esin Durmus; He He; Claire Cardie; Kathleen McKeown; | acl | 2022-05-17 |
478 | Towards Abstractive Grounded Summarization of Podcast Transcripts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The problem is exacerbated by speech disfluencies and recognition errors in transcripts of spoken language. In this paper, we explore a novel abstractive summarization method to alleviate these issues. |
Kaiqiang Song; Chen Li; Xiaoyang Wang; Dong Yu; Fei Liu; | acl | 2022-05-17 |
479 | Spurious Correlations in Reference-Free Evaluation of Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite promising recentresults, we find evidence that reference-freeevaluation metrics of summarization and dialoggeneration may be relying on spuriouscorrelations with measures such as word overlap,perplexity, and length. |
Esin Durmus; Faisal Ladhak; Tatsunori Hashimoto; | acl | 2022-05-17 |
480 | Length Control in Abstractive Summarization By Pretraining Information Selection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a length-aware attention mechanism (LAAM) to adapt the encoding of the source based on the desired length. |
Yizhu Liu; Qi Jia; Kenny Zhu; | acl | 2022-05-17 |
481 | Hallucinated But Factual! Inspecting The Factuality of Hallucinations in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel detection approach that separates factual from non-factual hallucinations of entities. |
Meng Cao; Yue Dong; Jackie Cheung; | acl | 2022-05-17 |
482 | ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper explores a deeper relationship between Transformer and numerical ODE methods. |
BEI LI et. al. | acl | 2022-05-17 |
483 | Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To fully explore the cascade structure and explainability of radiology report summarization, we introduce two innovations. First, we design a two-step approach: extractive summarization followed by abstractive summarization. Second, we additionally break down the extractive part into two independent tasks: extraction of salient (1) sentences and (2) keywords. |
Sanjeev Kumar Karn; Ning Liu; Hinrich Schuetze; Oladimeji Farri; | acl | 2022-05-17 |
484 | SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that it is possible to directly train a second-stage model performing re-ranking on a set of summary candidates. |
Mathieu Ravaut; Shafiq Joty; Nancy Chen; | acl | 2022-05-17 |
485 | Towards Making The Most of Cross-Lingual Transfer for Zero-Shot Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper demonstrates that multilingual pretraining and multilingual fine-tuning are both critical for facilitating cross-lingual transfer in zero-shot translation, where the neural machine translation (NMT) model is tested on source languages unseen during supervised training. Following this idea, we present SixT+, a strong many-to-English NMT model that supports 100 source languages but is trained with a parallel dataset in only six source languages. |
GUANHUA CHEN et. al. | acl | 2022-05-17 |
486 | An Imitation Learning Curriculum for Text Editing with Non-Autoregressive Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a framework for training non-autoregressive sequence-to-sequence models for editing tasks, where the original input sequence is iteratively edited to produce the output. |
Sweta Agrawal; Marine Carpuat; | acl | 2022-05-17 |
487 | SummN: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose SummN, a simple, flexible, and effective multi-stage framework for input texts that are longer than the maximum context length of typical pretrained LMs. |
YUSEN ZHANG et. al. | acl | 2022-05-17 |
488 | BRIO: Bringing Order to Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This assumption may lead to performance degradation during inference, where the model needs to compare several system-generated (candidate) summaries that have deviated from the reference summary. To address this problem, we propose a novel training paradigm which assumes a non-deterministic distribution so that different candidate summaries are assigned probability mass according to their quality. |
Yixin Liu; Pengfei Liu; Dragomir Radev; Graham Neubig; | acl | 2022-05-17 |
489 | RNSum: A Large-Scale Dataset for Automatic Release Note Generation Via Commit Logs Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a new dataset called RNSum, which contains approximately 82,000 English release notes and the associated commit messages derived from the online repositories in GitHub. |
Hisashi Kamezawa; Noriki Nishida; Nobuyuki Shimizu; Takashi Miyazaki; Hideki Nakayama; | acl | 2022-05-17 |
490 | Attention Temperature Matters in Abstractive Summarization Distillation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we find simply manipulating attention temperatures in Transformers can make pseudo labels easier to learn for student models. |
Shengqiang Zhang; Xingxing Zhang; Hangbo Bao; Furu Wei; | acl | 2022-05-17 |
491 | ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present ViT5, a pretrained Transformer-based encoder-decoder model for the Vietnamese language. |
Long Phan; Hieu Tran; Hieu Nguyen; Trieu H. Trinh; | arxiv-cs.CL | 2022-05-13 |
492 | Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, state-of-the-art NLI models perform poorly in this context due to their inability to generalize to the target task. In this work, we show that NLI models can be effective for this task when the training data is augmented with high-quality task-oriented examples. |
Prasetya Ajie Utama; Joshua Bambrick; Nafise Sadat Moosavi; Iryna Gurevych; | arxiv-cs.CL | 2022-05-12 |
493 | Few-shot Mining of Naturally Occurring Inputs and Outputs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Creating labeled natural language training data is expensive and requires significant human effort. We mine input output examples from large corpora using a supervised mining … |
Mandar Joshi; Terra Blevins; Mike Lewis; Daniel S. Weld; Luke Zettlemoyer; | arxiv-cs.CL | 2022-05-09 |
494 | Deep Reinforcement and Transfer Learning for Abstractive Text Summarization: A Review Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ayham Alomari; Norisma Idris; Aznul Qalid Md Sabri; Izzat Alsmadi; | Comput. Speech Lang. | |
495 | Introducing The Welsh Text Summarisation Dataset and Baseline Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: As part of the effort to increase the availability of Welsh digital technology, this paper introduces the first Welsh summarisation dataset, which we provide freely for research purposes to help advance the work on Welsh text summarization. |
Ignatius Ezeani; Mahmoud El-Haj; Jonathan Morris; Dawn Knight; | arxiv-cs.CL | 2022-05-05 |
496 | Masked Summarization to Generate Factually Inconsistent Summaries for Improved Factual Consistency Checking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to generate factually inconsistent summaries using source texts and reference summaries with key information masked. |
Hwanhee Lee; Kang Min Yoo; Joonsuk Park; Hwaran Lee; Kyomin Jung; | arxiv-cs.CL | 2022-05-04 |
497 | Efficient Few-Shot Fine-Tuning for Opinion Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In addition, generically pre-trained models are often not accustomed to the specifics of customer reviews and, after fine-tuning, yield summaries with disfluencies and semantic mistakes. To address these problems, we utilize an efficient few-shot method based on adapters which, as we show, can easily store in-domain knowledge. |
Arthur Bražinskas; Ramesh Nallapati; Mohit Bansal; Markus Dreyer; | arxiv-cs.CL | 2022-05-04 |
498 | SOSum: A Dataset of Stack Overflow Post Summaries IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Stack Overflow (SO) is becoming an indispensable part of modern software development workflow. However, given the limited time, attention, and memory capacity of programmers, … |
Bonan Kou; Yifeng Di; Muhao Chen; Tianyi Zhang; | 2022 IEEE/ACM 19th International Conference on Mining … | 2022-05-01 |
499 | Key Phrase Aware Transformer for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shuaiqi Liu; Jiannong Cao; Ruosong Yang; Zhiyuan Wen; | Inf. Process. Manag. | 2022-05-01 |
500 | Large-Scale Multi-Document Summarization with Information Extraction and Compression Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We develop an abstractive summarization framework independent of labeled data for multiple heterogeneous documents. |
Ning Wang; Han Liu; Diego Klabjan; | arxiv-cs.CL | 2022-05-01 |
501 | Faithful to The Document or to The World? Mitigating Hallucinations Via Entity-linked Knowledge in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Methods have been proposed to address this scenario by ultimately improving `faithfulness’ to the source document, but in reality, there is a large portion of entities in the gold reference targets that are not directly in the source. In this work, we show that these entities are not aberrations, but they instead require utilizing external world knowledge to infer reasoning paths from entities in the source. |
Yue Dong; John Wieting; Pat Verga; | arxiv-cs.CL | 2022-04-28 |
502 | Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this way, it is possible to translate the English dataset to other languages and obtain different sets of labels again using heuristics. To fully leverage the information of these different sets of labels, we propose NLSSum (Neural Label Search for Summarization), which jointly learns hierarchical weights for these different sets of labels together with our summarization model. |
RUIPENG JIA et. al. | arxiv-cs.CL | 2022-04-28 |
503 | WikiMulti: A Corpus for Cross-Lingual Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce WikiMulti – a new dataset for cross-lingual summarization based on Wikipedia articles in 15 languages. |
Pavel Tikhonov; Valentin Malykh; | arxiv-cs.CL | 2022-04-23 |
504 | A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we conduct a systematic survey with comparisons and discussions of various non-autoregressive translation (NAT) models from different aspects. |
YISHENG XIAO et. al. | arxiv-cs.CL | 2022-04-20 |
505 | A Survey on Neural Abstractive Summarization Methods and Factual Consistency of Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic summarization is the process of shortening a set of textual data computationally, to create a subset (a summary) that represents the most important pieces of information … |
Meng Cao; | arxiv-cs.CL | 2022-04-20 |
506 | Factual Error Correction for Abstractive Summaries Using Entity Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an efficient factual error correction system RFEC based on entities retrieval post-editing process. |
HWANHEE LEE et. al. | arxiv-cs.CL | 2022-04-18 |
507 | Summarization with Graphical Elements Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This is in line with what we know from the psycholinguistics literature about how humans process text. Motivated from these two angles, we propose a new task: summarization with graphical elements, and we verify that these summaries are helpful for a critical mass of people. |
Maartje ter Hoeve; Julia Kiseleva; Maarten de Rijke; | arxiv-cs.CL | 2022-04-15 |
508 | FactGraph: Evaluating Factuality in Summarization with Semantic Graph Representations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent works have shown promising improvements in factuality error identification using text or dependency arc entailments; however, they do not consider the entire semantic graph simultaneously. To this end, we propose FactGraph, a method that decomposes the document and the summary into structured meaning representations (MR), which are more suitable for factuality evaluation. |
Leonardo F. R. Ribeiro; Mengwen Liu; Iryna Gurevych; Markus Dreyer; Mohit Bansal; | arxiv-cs.CL | 2022-04-13 |
509 | Make The Most of Prior Data: A Solution for Interactive Text Summarization with Preference Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce a new framework to train summarization models with preference feedback interactively. |
DUY-HUNG NGUYEN et. al. | arxiv-cs.AI | 2022-04-11 |
510 | Evaluation of Automatic Text Summarization Using Synthetic Facts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Two main problems with current summarization methods are well known: evaluation and factual consistency. To address these issues, we propose a new automatic reference-less text summarization evaluation system that can measure the quality of any text summarization model with a set of generated facts based on factual consistency, comprehensiveness, and compression rate. |
Jay Ahn; Foaad Khosmood; | arxiv-cs.CL | 2022-04-11 |
511 | Beam Decoding with Controlled Patience Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Text generation with beam search has proven successful in a wide range of applications. The commonly-used implementation of beam decoding follows a first come, first served … |
JUNGO KASAI et. al. | ArXiv | 2022-04-11 |
512 | Towards Automatically Generating Release Notes Using Extractive Summarization Technique Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For example, we collect data from GitHub with over 1,900 releases, among them 37% of the release notes are empty. We propose an automatic generate release notes approach based on the commit messages and merge pull-request (PR) titles to mitigate this problem. |
Sristy Sumana Nath; Banani Roy; | arxiv-cs.SE | 2022-04-11 |
513 | A Call for Clarity in Beam Search: How It Works and When It Stops Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We point out that, though largely overlooked in the literature, the commonly-used implementation of beam decoding (e.g., Hugging Face Transformers and fairseq) uses a first come, first served heuristic: it keeps a set of already completed sequences over time steps and stops when the size of this set reaches the beam size. Based on this finding, we introduce a patience factor, a simple modification to this beam decoding implementation, that generalizes the stopping criterion and provides flexibility to the depth of search. |
JUNGO KASAI et. al. | arxiv-cs.CL | 2022-04-11 |
514 | PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To support it, we designed a novel soft prompts architecture coupled with a prompt pre-training plus fine-tuning paradigm that is effective and tunes only extremely light parameters. |
XIAOCHEN LIU et. al. | arxiv-cs.CL | 2022-04-09 |
515 | Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have … |
ERKUT ERDEM et. al. | J. Artif. Intell. Res. | 2022-04-06 |
516 | Abstractive Summarization of Hospitalisation Histories with Transformer Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we present a novel approach to abstractive summarization of patient hospitalisation histories. |
Alexander Yalunin; Dmitriy Umerenkov; Vladimir Kokh; | arxiv-cs.CL | 2022-04-05 |
517 | Applying Automatic Text Summarization for Fake News Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present an approach to the problem that combines the power of transformer-based language models while simultaneously addressing one of their inherent problems. |
Philipp Hartl; Udo Kruschwitz; | arxiv-cs.CL | 2022-04-04 |
518 | Improving The Factual Accuracy of Abstractive Clinical Text Summarization Using Multi-Objective Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a framework for improving the factual accuracy of abstractive summarization of clinical text using knowledge-guided multi-objective optimization. |
Amanuel Alambo; Tanvi Banerjee; Krishnaprasad Thirunarayan; Mia Cajita; | arxiv-cs.CL | 2022-04-02 |
519 | A Multi-Level Optimization Framework for End-to-End Text Augmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text augmentation is an effective technique in alleviating overfitting in NLP tasks. In existing methods, text augmentation and downstream tasks are mostly performed separately. … |
Sai Ashish Somayajula; Linfeng Song; P. Xie; | Transactions of the Association for Computational … | 2022-04-01 |
520 | A Topic Modeled Unsupervised Approach to Single Document Extractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ridam Srivastava; Prabhav Singh; K. Rana; Vineet Kumar; | Knowl. Based Syst. | 2022-04-01 |
521 | Speculative Decoding: Lossless Speedup of Autoregressive Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Different from some previous work accelerating autoregressive translation (AT) at the sacrifice of quality, we propose Speculative Decoding (SpecDec) — a novel decoding paradigm inspired by speculative execution in computer architecture, which combines respective advantages of AT and non-autoregressive translation (NAT) for lossless speedup of translation. |
Heming Xia; Tao Ge; Si-Qing Chen; Furu Wei; Zhifang Sui; | arxiv-cs.CL | 2022-03-30 |
522 | Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: We propose Speculative Decoding (SpecDec), for the first time ever, to formally study exploiting the idea of speculative execution to accelerate autoregressive (AR) decoding. … |
HEMING XIA et. al. | Conference on Empirical Methods in Natural Language … | 2022-03-30 |
523 | An Overview of Indian Language Datasets Used for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we survey Text Summarization (TS) datasets in Indian Languages (ILs), which are also low-resource languages (LRLs). |
Shagun Sinha; Girish Nath Jha; | arxiv-cs.CL | 2022-03-30 |
524 | Engineering Document Summarization: A Bidirectional Language Model-Based Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this study, the extractive summarization using sentence embeddings generated by the finetuned BERT (Bidirectional Encoder Representations from Transformers) models and the … |
Y. Qiu; Yang Jin; | J. Comput. Inf. Sci. Eng. | 2022-03-29 |
525 | Entity-driven Fact-aware Abstractive Summarization of Biomedical Literature Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose an entity-driven fact-aware framework for training end-to-end transformer-based encoder-decoder models for abstractive summarization of biomedical articles. |
Amanuel Alambo; Tanvi Banerjee; Krishnaprasad Thirunarayan; Michael Raymer; | arxiv-cs.CL | 2022-03-29 |
526 | AraBART: A Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we propose AraBART, the first Arabic model in which the encoder and the decoder are pretrained end-to-end, based on BART. |
Moussa Kamal Eddine; Nadi Tomeh; Nizar Habash; Joseph Le Roux; Michalis Vazirgiannis; | arxiv-cs.CL | 2022-03-21 |
527 | Meta-X_{NLG}: A Meta-Learning Approach Based on Language Clustering for Zero-Shot Cross-Lingual Transfer and Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, the NLP community has witnessed a rapid advancement in multilingual and cross-lingual transfer research where the supervision is transferred from high-resource languages … |
Kaushal Kumar Maurya; M. Desarkar; | ArXiv | 2022-03-19 |
528 | Meta-X$_{NLG}$: A Meta-Learning Approach Based on Language Clustering for Zero-Shot Cross-Lingual Transfer and Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel meta-learning framework (called Meta-X$_{NLG}$) to learn shareable structures from typologically diverse languages based on meta-learning and language clustering. |
Kaushal Kumar Maurya; Maunendra Sankar Desarkar; | arxiv-cs.CL | 2022-03-19 |
529 | HiStruct+: Improving Extractive Text Summarization with Hierarchical Structure Information IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel approach to formulate, extract, encode and inject hierarchical structure information explicitly into an extractive summarization model based on a pre-trained, encoder-only Transformer language model (HiStruct+ model), which improves SOTA ROUGEs for extractive summarization on PubMed and arXiv substantially. |
Qian Ruan; Malte Ostendorff; Georg Rehm; | arxiv-cs.CL | 2022-03-17 |
530 | Don’t Say What You Don’t Know: Improving The Consistency of Abstractive Summarization By Constraining Beam Search IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization systems today produce fluent and relevant output, but often “hallucinate” statements not supported by the source text. We analyze the connection between … |
DANIEL KING et. al. | ArXiv | 2022-03-16 |
531 | Don’t Say What You Don’t Know: Improving The Consistency of Abstractive Summarization By Constraining Beam Search Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Based on our findings, we present PINOCCHIO, a new decoding method that improves the consistency of a transformer-based abstractive summarizer by constraining beam search to avoid hallucinations. |
DANIEL KING et. al. | arxiv-cs.CL | 2022-03-16 |
532 | Unsupervised Extractive Opinion Summarization Using Sparse Coding IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present Semantic Autoencoder (SemAE) to perform extractive opinion summarization in an unsupervised manner. |
Somnath Basu Roy Chowdhury; Chao Zhao; Snigdha Chaturvedi; | arxiv-cs.CL | 2022-03-15 |
533 | Long Document Summarization with Top-down and Bottom-up Inference IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a principled inference framework to improve summarization models on these two aspects. |
BO PANG et. al. | arxiv-cs.CL | 2022-03-14 |
534 | Uncertainty Estimation for Language Reward Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Language models can learn a range of capabilities from unsupervised training on text corpora. |
Adam Gleave; Geoffrey Irving; | arxiv-cs.CL | 2022-03-14 |
535 | SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that it is possible to directly train a second-stage model performing re-ranking on a set of summary candidates. |
Mathieu Ravaut; Shafiq Joty; Nancy F. Chen; | arxiv-cs.CL | 2022-03-13 |
536 | Deep Learning-based Extractive Text Summarization with Word-level Attention Mechanism IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mahak Gambhir; Vishal Gupta; | Multimedia Tools and Applications | 2022-03-12 |
537 | Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this survey, we provide a systematic overview of the research progress on the faithfulness problem of NLG, including problem analysis, evaluation metrics and optimization methods. |
WEI LI et. al. | arxiv-cs.CL | 2022-03-10 |
538 | A Survey of Implicit Discourse Relation Recognition Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In each solution category, we present and analyze the most representative methods, including their origins, ideas, strengths and weaknesses. |
Wei Xiang; Bang Wang; | arxiv-cs.CL | 2022-03-06 |
539 | An Approach of Syntactical Text Graph Representation Learning for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tham Vo; | International Journal of Intelligent Robotics and … | 2022-03-05 |
540 | ClueGraphSum: Let Key Clues Guide The Cross-Lingual Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous studies on CLS mainly take pipeline methods or train the end-to-end model using the translated parallel data. |
SHUYU JIANG et. al. | arxiv-cs.CL | 2022-03-05 |
541 | Follow The Timeline! Generating An Abstractive and Extractive Timeline Summary in Chronological Order Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Today, timestamped web documents related to a general news query flood the Internet, and timeline summarization targets this concisely by summarizing the evolution trajectory of … |
XIUYING CHEN et. al. | ACM Transactions on Information Systems | 2022-03-05 |
542 | Automatic Text Summarization Methods: A Comprehensive Review IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: One of the most pressing issues that have arisen due to the rapid growth of the Internet is known as information overloading. Simplifying the relevant information in the form of a … |
Divakar Yadav; Jalpa J Desai; A. Yadav; | ArXiv | 2022-03-03 |
543 | Controlling The Focus of Pretrained Language Generation Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work aims to develop a control mechanism by which a user can select spans of context as highlights for the model to focus on, and generate relevant output. |
Jiabao Ji; Yoon Kim; James Glass; Tianxing He; | arxiv-cs.AI | 2022-03-02 |
544 | A Multi-objective Memetic Algorithm for Query-oriented Text Summarization: Medicine Texts As A Case Study IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jesús M. Sánchez-Gómez; M. A. Vega-Rodríguez; C. J. Pérez; | Expert Syst. Appl. | 2022-03-01 |
545 | RankSum – An Unsupervised Extractive Text Summarization Based on Rank Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Akanksha Joshi; Eduardo FIDALGO; Enrique Alegre; R. Alaíz-Rodríguez; | Expert Syst. Appl. | 2022-03-01 |
546 | Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts Vs. Comment Pools in Three Languages Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s … |
I. Blekanov; N. Tarasov; Svetlana Bodrunova; | Future Internet | 2022-02-23 |
547 | Learning Cluster Patterns for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For this, we propose a novel clustering transformer layer between the encoder and the decoder, which first generates two clusters of salient and non-salient vectors, and then normalizes and shrinks the clusters to make them apart in the latent space. |
Sung-Guk Jo; Jeong-Jae Kim; Byung-Won On; | arxiv-cs.CL | 2022-02-22 |
548 | Hierarchical Sliding Inference Generator for Question-driven Abstractive Answer Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization on non-factoid question answering (NQA) aims at identifying the core information of redundant answer guidance using questions, which can dramatically improve … |
Bing Li; Peng Yang; Hanlin Zhao; Penghui Zhang; Zijian Liu; | ACM Transactions on Information Systems | 2022-02-14 |
549 | Sequence-to-Sequence Resources for Catalan Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce sequence-to-sequence language resources for Catalan, a moderately under-resourced language, towards two tasks, namely: Summarization and Machine Translation (MT). |
Ona de Gibert; Ksenia Kharitonova; Blanca Calvo Figueras; Jordi Armengol-Estapé; Maite Melero; | arxiv-cs.CL | 2022-02-14 |
550 | Differentiable N-gram Objective on Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present differentiable n-gram objectives, attempting to alleviate the discrepancy between training criterion and evaluating criterion. |
Yunqi Zhu; Xuebing Yang; Yuanyuan Wu; Mingjin Zhu; Wensheng Zhang; | arxiv-cs.CL | 2022-02-08 |
551 | Target-Side Data Augmentation for Sequence Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We study the data augmentation for target-side conditional input of autoregressive sequence generation and propose a new method to build soft synthetic data. |
SHUFANG XIE et. al. | iclr | 2022-02-08 |
552 | Towards A Unified View of Parameter-Efficient Transfer Learning IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a unified framework for several state-of-the-art parameter-efficient tuning methods, |
Junxian He; Chunting Zhou; Xuezhe Ma; Taylor Berg-Kirkpatrick; Graham Neubig; | iclr | 2022-02-08 |
553 | DictFormer: Tiny Transformer with Shared Dictionary Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose DictFormer with efficient shared dictionary to provide a compact, fast, and accurate transformer model. |
Qian Lou; Ting Hua; Yen-Chang Hsu; Yilin Shen; Hongxia Jin; | iclr | 2022-02-08 |
554 | Semantic Self-Segmentation for Abstractive Summarization of Long Documents in Low-Resource Regimes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel semantic self-segmentation (Se3) approach for long document summarization to address the critical problems of low-resource regimes, namely to process inputs longer than the GPU memory capacity and produce accurate summaries despite the availability of only a few dozens of training instances. |
Gianluca Moro; Luca Ragazzi; | aaai | 2022-02-07 |
555 | Survey of Hallucination in Natural Language Generation IF:7 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this survey, we thus provide a broad overview of the research progress and challenges in the hallucination problem in NLG. |
ZIWEI JI et. al. | arxiv-cs.CL | 2022-02-07 |
556 | Hierarchical Heterogeneous Graph Attention Network for Syntax-Aware Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we essentially incorporate the constituent structure into the single document summarization via the Graph Neural Networks to learn the semantic meaning of tokens. |
Zixing Song; Irwin King; | aaai | 2022-02-07 |
557 | Improving Neural Cross-Lingual Abstractive Summarization Via Employing Optimal Transport Distance for Knowledge Distillation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The matter worsens when performing on languages with separate morphological or structural features, making the cross-lingual alignment more challenging, resulting in the performance drop. To overcome this problem, we propose a novel Knowledge-Distillation-based framework for Cross-Lingual Summarization, seeking to explicitly construct cross-lingual correlation by distilling the knowledge of the monolingual summarization teacher into the cross-lingual summarization student. |
Thong Thanh Nguyen; Anh Tuan Luu; | aaai | 2022-02-07 |
558 | Sequence Level Contrastive Learning for Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In text summarization, the output summary is a shorter form of the input document and they have similar meanings. In this paper, we propose a contrastive learning model for supervised abstractive text summarization, where we view a document, its gold summary and its model generated summaries as different views of the same mean representation and maximize the similarities between them during training. |
Shusheng Xu; Xingxing Zhang; Yi Wu; Furu Wei; | aaai | 2022-02-07 |
559 | SummaryLens — A Smartphone App for Exploring Interactive Use of Automated Text Summarization in Everyday Life Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present SummaryLens, a concept and prototype for a mobile tool that leverages automated text summarization to enable users to quickly scan and summarize physical text documents. |
Karim Benharrak; Florian Lehmann; Hai Dang; Daniel Buschek; | arxiv-cs.HC | 2022-02-04 |
560 | Locally Typical Sampling IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we posit that the abstraction of natural language generation as a discrete stochastic process–which allows for an information-theoretic analysis–can provide new insights into the behavior of probabilistic language generators, e.g., why high-probability texts can be dull or repetitive. |
Clara Meister; Tiago Pimentel; Gian Wiher; Ryan Cotterell; | arxiv-cs.CL | 2022-02-01 |
561 | IoTSAX: A Dynamic Abstractive Entity Summarization Approach With Approximation and Embedding-Based Reasoning Rules in Publish/Subscribe Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Users are interested in entity information and may use paradigms like publish/subscribe systems in Internet of Things (IoT), where entity-centric data comes from multiple sources. … |
Niki Pavlopoulou; E. Curry; | IEEE Internet of Things Journal | 2022-02-01 |
562 | Submodularity In Machine Learning and Artificial Intelligence IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this manuscript, we offer a gentle review of submodularity and supermodularity and their properties. |
Jeff Bilmes; | arxiv-cs.LG | 2022-01-31 |
563 | FCSF-TABS: Two-stage Abstractive Summarization with Fact-aware Reinforced Content Selection and Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View |
MENGLI ZHANG et. al. | Neural Computing and Applications | 2022-01-30 |
564 | Unsupervised Multi-Granularity Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose the first unsupervised multi-granularity summarization framework, GranuSum. |
MING ZHONG et. al. | arxiv-cs.CL | 2022-01-29 |
565 | Performance Study on Extractive Text Summarization Using BERT Models IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The task of summarization can be categorized into two methods, extractive and abstractive. Extractive summarization selects the salient sentences from the original document to … |
Shehab Abdel-Salam; Ahmed Rafea; | Inf. | 2022-01-28 |
566 | WIDAR — Weighted Input Document Augmented ROUGE Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The task of automatic text summarization has gained a lot of traction due to the recent advancements in machine learning techniques. However, evaluating the quality of a generated … |
Raghav Jain; Vaibhav Mavi; Anubhav Jangra; Sriparna Saha; | arxiv-cs.CL | 2022-01-23 |
567 | Exploiting Comments Information to Improve Legal Public Opinion News Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yuxin Huang; Zheng Yu; Yanchao Xiang; Zhiqiang Yu; Junjun Guo; | Frontiers of Computer Science | 2022-01-22 |
568 | SciBERTSUM: Extractive Summarization for Scientific Documents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce SciBERTSUM, our summarization framework designed for the summarization of long documents like scientific papers with more than 500 sentences. |
Athar Sefid; C Lee Giles; | arxiv-cs.CL | 2022-01-20 |
569 | Klexikon: A German Dataset for Joint Summarization and Simplification IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Simultaneously, resources for non-English languages are scarce in general and prohibitive for training new solutions. To tackle this problem, we pose core requirements for a system that can jointly summarize and simplify long source documents. |
Dennis Aumiller; Michael Gertz; | arxiv-cs.CL | 2022-01-18 |
570 | ExtraPhrase: Efficient Data Augmentation for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a low-cost and effective strategy, ExtraPhrase, to augment training data for abstractive summarization tasks. |
Mengsay Loem; Sho Takase; Masahiro Kaneko; Naoaki Okazaki; | arxiv-cs.CL | 2022-01-14 |
571 | Abstractive Text Summarization and New Large-scale Datasets for Agglutinative Languages Turkish and Hungarian Related Papers Related Patents Related Grants Related Venues Related Experts View |
Batuhan Baykara; Tunga Güngör; | Language Resources and Evaluation | 2022-01-10 |
572 | An Unsupervised Masking Objective for Abstractive Multi-Document News Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that a simple unsupervised masking objective can approach near supervised performance on abstractive multi-document news summarization. |
Nikolai Vogler; Songlin Li; Yujie Xu; Yujian Mi; Taylor Berg-Kirkpatrick; | arxiv-cs.CL | 2022-01-06 |
573 | Document Vector Embedding Based Extractive Text Summarization System for Hindi and English Text Related Papers Related Patents Related Grants Related Venues Related Experts View |
R. Rani; D. K. Lobiyal; | Applied Intelligence | 2022-01-05 |
574 | A Comprehensive Review of Arabic Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The explosion of online and offline data has changed how we gather, evaluate, and understand data. It is frequently difficult and time-consuming to comprehend large text documents … |
Asmaa H. Elsaid; Ammar Mohammed; L. F. Ibrahim; M. Sakre; | IEEE Access | 2022-01-01 |
575 | MedicalSum: A Guided Clinical Abstractive Summarization Model for Generating Medical Reports from Patient-Doctor Conversations IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We introduce MedicalSum , a Transformer-001 based sequence-to-sequence architecture for 002 summarizing medical conversations by integrat-003 ing medical domain knowledge from the … |
George Michalopoulos; Kyle Williams; Gagandeep Singh; Thomas Lin; | Conference on Empirical Methods in Natural Language … | 2022-01-01 |
576 | GenCompareSum: A Hybrid Unsupervised Summarization Method Using Salience IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Text summarization (TS) is an important NLP task. Pre-trained Language Models (PLMs) have been used to improve the performance of TS. However, PLMs are limited by their need of … |
Jennifer A Bishop; Qianqian Xie; S. Ananiadou; | Workshop on Biomedical Natural Language Processing | 2022-01-01 |
577 | Fact-Driven Abstractive Summarization By Utilizing Multi-Granular Multi-Relational Knowledge Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization generates a concise summary to capture the key ideas of the source text. This task underpins important applications like information retrieval, document … |
QIANREN MAO et. al. | IEEE/ACM Transactions on Audio, Speech, and Language … | 2022-01-01 |
578 | BanglaNLG: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This work presents ‘BanglaNLG,’ a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language in the web … |
Abhik Bhattacharjee; Tahmid Hasan; Wasi Uddin Ahmad; Rifat Shahriyar; | ArXiv | 2022-01-01 |
579 | An Approach for Extractive Text Summarization Using Fuzzy Evolutionary and Clustering Algorithms IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Pradeepika Verma; Anshul Verma; Sukomal Pal; | Appl. Soft Comput. | 2022-01-01 |
580 | Automatic Text Summarization for Moroccan Arabic Dialect Using An Artificial Intelligence Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
Kamel Gaanoun; Naira Abdou Mohamed; Anass Allak; Imade Benelallam; | Conference on Business Informatics | 2022-01-01 |
581 | Improving Unsupervised Extractive Summarization By Jointly Modeling Facet and Redundancy Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised extractive summarization aims to extract salient sentences from documents without labeled corpus. Existing methods are mostly graph-based by computing sentence … |
Xinnian Liang; Jing Li; Shuangzhi Wu; Mu Li; Zhoujun Li; | IEEE/ACM Transactions on Audio, Speech, and Language … | 2022-01-01 |
582 | Difformer: Empowering Diffusion Model on Embedding Space for Text Generation IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Diffusion models have achieved state-of-the-art synthesis quality on visual and audio tasks, and recent works adapt them to textual data by diffusing on the embedding space. But … |
ZHUJIN GAO et. al. | ArXiv | 2022-01-01 |
583 | Quantifying Clinical Outcome Measures in Patients with Epilepsy Using The Electronic Health Record Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A wealth of important clinical information lies untouched in the Electronic Health Record, often in the form of unstructured textual documents. For patients with Epilepsy, such … |
Kevin Xie; B. Litt; D. Roth; C. Ellis; | Workshop on Biomedical Natural Language Processing | 2022-01-01 |
584 | Few-shot Fine-tuning SOTA Summarization Models for Medical Dialogues IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization of medical dialogues presents a challenge for standard training approaches, given the paucity of suitable datasets. We explore the performance of … |
David Fraile Navarro; M. Dras; S. Berkovsky; | North American Chapter of the Association for Computational … | 2022-01-01 |
585 | Enhancing Biomedical Scientific Reviews Summarization with Graph-based Factual Evidence Extracted from Papers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: : Combining structured knowledge and neural language models to tackle natural language processing tasks is a recent research trend that catalyzes community attention. This … |
Giacomo Frisoni; Paolo Italiani; Francesco Boschi; G. Moro; | International Conference on Data Technologies and … | 2022-01-01 |
586 | Zero-Shot Opinion Summarization with GPT-3 IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Very large language models such as GPT-3 have shown impressive performance across a wide variety of tasks, including text summarization. In this paper, we show that this strong … |
Adithya Bhaskar; Alexander R. Fabbri; Greg Durrett; | ArXiv | 2022-01-01 |
587 | Semantic-Preserving Abstractive Text Summarization with Siamese Generative Adversarial Net Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose a novel siamese generative adver sarial net for abstractive text summarization (SSPGAN), which can preserve the main se mantics of the source text. Different from … |
Xin Sheng; Linli Xu; Yinlong Xu; Deqiang Jiang; Bo Ren; | NAACL-HLT | 2022-01-01 |
588 | Summarization of Text and Image Captioning in Information Retrieval Using Deep Learning Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automated information retrieval and text summarization concept is a difficult process in natural language processing because of the infrequent structure and high complexity of the … |
P. Mahalakshmi; N. Fatima; | IEEE Access | 2022-01-01 |
589 | StarSum: A Star Architecture Based Model for Extractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive summarization aims to produce a concise summary while retaining the key information through the way of selecting sentences from the original document. Under such … |
Kaile Shi; Xiaoyan Cai; Libin Yang; Jintao Zhao; Shirui Pan; | IEEE/ACM Transactions on Audio, Speech, and Language … | 2022-01-01 |
590 | Ensembled Approach for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Minakshi Tomer; Dishant Rathie; Manoj Kumar; | 2022-01-01 | |
591 | Entity-based De-noising Modeling for Controllable Dialogue Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although fine-tuning pre-trained backbones produces fluent and grammatically-correct text in various language generation tasks, factual consistency in abstractive summarization … |
Zhengyuan Liu; Nancy F. Chen; | SIGDIAL Conferences | 2022-01-01 |
592 | Revisiting Automatic Evaluation of Extractive Summarization Task: Can We Do Better Than ROUGE? IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It has been the norm for a long time to evaluate automated summarization tasks using the popular ROUGE metric. Although several studies in the past have highlighted the … |
Mousumi Akter; Naman Bansal; Shubhra (Santu) Karmaker; | FINDINGS | 2022-01-01 |
593 | Intelligent RFQ Summarization Using Natural Language Processing, Text Mining, and Machine Learning Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Request for quotation (RFQ) is a lengthy document soliciting vendor products and services according to rigid specifications. This research develops an integrated natural language … |
A. Trappey; Ai-Che Chang; C. Trappey; Jack Y. C. Chang Chien; | J. Glob. Inf. Manag. | 2022-01-01 |
594 | Goal-Directed Extractive Summarization of Financial Reports Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we address this challenge by modeling 10-K report summarization using a goal-directed setting where we leverage summaries with labeled goal-related data for the stock buy/sell classification goal. |
Yash Agrawal; Vivek Anand; Manish Gupta; S Arunachalam; Vasudeva Varma; | cikm | 2021-12-30 |
595 | Summarizing Long-Form Document with Rich Discourse Information Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the two deficiencies, we propose HEROES, a novel extractive summarization model for summarizing long-form documents with rich discourse structural information. |
Tianyu Zhu; Wen Hua; Jianfeng Qu; Xiaofang Zhou; | cikm | 2021-12-30 |
596 | Boosting Few-shot Abstractive Summarization with Auxiliary Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we employ BART as the base sequence-to-sequence model and incorporate the main and auxiliary tasks under the multi-task framework. |
Qiwei Bi; Haoyuan Li; Hanfang Yang; | cikm | 2021-12-30 |
597 | TFW2V: An Enhanced Document Similarity Method for The Morphologically Rich Finnish Language Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: At the same time, we propose a simple method, TFW2V, which shows high efficiency in handling both long text documents and limited amounts of data. |
Quan Duong; Mika Hämäläinen; Khalid Alnajjar; | arxiv-cs.CL | 2021-12-23 |
598 | Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: The Query-Focused Text Summarization (QFTS) task aims at building systems that generate the summary of the text document(s) based on the given query. A key challenge in addressing … |
Md Tahmid Rahman Laskar; Enamul Hoque; J. Huang; | Computational Linguistics | 2021-12-22 |
599 | Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we address this challenge by exploring a series of domain adaptation techniques. |
Md Tahmid Rahman Laskar; Enamul Hoque; Jimmy Xiangji Huang; | arxiv-cs.CL | 2021-12-22 |
600 | An ASP-based Approach to Answering Natural Language Questions for Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we describe the CASPR system that we have developed to automate the task of answering natural language questions given English text. |
Dhruva Pendharkar; Kinjal Basu; Farhad Shakerin; Gopal Gupta; | arxiv-cs.CL | 2021-12-21 |
601 | May The Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel supervised approach of a copy network that helps the model decide which words need to be copied and which need to be generated. |
Sanghyuk Choi; Jeong-in Hwang; Hyungjong Noh; Yeonsoo Lee; | arxiv-cs.CL | 2021-12-20 |
602 | Word Graph Guided Summarization for Radiology Findings IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel method for automatic impression generation, where a word graph is constructed from the findings to record the critical words and their relations, then a Word Graph guided Summarization model (WGSum) is designed to generate impressions with the help of the word graph. |
JINPENG HU et. al. | arxiv-cs.CL | 2021-12-18 |
603 | Topic-Aware Encoding for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, a neural topic model is added in the neural-based sentence-level representation learning to adequately consider the central topic information for capturing the critical content in the original document. |
Mingyang Song; Liping Jing; | arxiv-cs.CL | 2021-12-17 |
604 | CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we provide a typology of factual errors with annotation data to highlight the types of errors and move away from a binary understanding of factuality. |
XIANGRU TANG et. al. | arxiv-cs.CL | 2021-12-16 |
605 | QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we conduct an extensive comparison of entailment and QA-based metrics, demonstrating that carefully choosing the components of a QA-based metric, especially question generation and answerability classification, is critical to performance. |
Alexander R. Fabbri; Chien-Sheng Wu; Wenhao Liu; Caiming Xiong; | arxiv-cs.CL | 2021-12-15 |
606 | Learning Rich Representation of Keyphrases from Text IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we explore how to train task-specific language models aimed towards learning rich representation of keyphrases from text documents. |
Mayank Kulkarni; Debanjan Mahata; Ravneet Arora; Rajarshi Bhowmik; | arxiv-cs.CL | 2021-12-15 |
607 | Generating Topic-Preserving Synthetic News Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The text generation methods have witnessed great success in text summarization, machine translation, and synthetic news generation. However, these techniques may be abused to … |
Ahmadreza Mosallanezhad; Kai Shu; Huan Liu; | 2021 IEEE International Conference on Big Data (Big Data) | 2021-12-15 |
608 | DSGPT: Domain-Specific Generative Pre-Training of Transformers for Text Generation in E-commerce Title and Review Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel domain-specific generative pre-training (DS-GPT) method for text generation and apply it to the product titleand review summarization problems on E-commerce mobile display.First, we adopt a decoder-only transformer architecture, which fitswell for fine-tuning tasks by combining input and output all to-gether. |
XUEYING ZHANG et. al. | arxiv-cs.CL | 2021-12-15 |
609 | Reinforced Abstractive Summarization with Adaptive Length Controlling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an \textbf{A}daptive \textbf{L}ength \textbf{C}ontrolling \textbf{O}ptimization (\textbf{ALCO}) method to leverage two-stage abstractive summarization model via reinforcement learning. |
Mingyang Song; Yi Feng; Liping Jing; | arxiv-cs.CL | 2021-12-14 |
610 | Generating Fluent Fact Checking Explanations with Unsupervised Post-Editing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Fact-checking systems have become important tools to verify fake and misguiding news. These systems become more trustworthy when human-readable explanations accompany the veracity … |
Shailza Jolly; Pepa Atanasova; Isabelle Augenstein; | Inf. | 2021-12-13 |
611 | A New Sentence Extraction Strategy for Unsupervised Extractive Summarization Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To improve the feature distribution and to decrease the mutual information of summarization sentences, we propose a new sentence extraction strategy which can be applied to existing unsupervised extractive methods. |
Dehao Tao; Yingzhu Xiong; Zhongliang Yang; Yongfeng Huang; | arxiv-cs.CL | 2021-12-06 |
612 | CO2Sum:Contrastive Learning for Factual-Consistent Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we provide a factual-consistent solution from the perspective of contrastive learning, which is a natural extension of previous works. |
WEI LIU et. al. | arxiv-cs.CL | 2021-12-02 |
613 | Query-focused Abstractive Summarization Via Question-answering Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is a task that creates a short version of a document while preserving the main content. In the age of information explosion, how to obtain the content that … |
Jiachen Du; Yang Gao; | 2021 IEEE International Conference on Big Knowledge (ICBK) | 2021-12-01 |
614 | Multilayer Encoder and Single-layer Decoder for Abstractive Arabic Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Dima Suleiman; A. Awajan; | Knowl. Based Syst. | 2021-12-01 |
615 | Evaluating Code Summarization with Improved Correlation with Human Assessment Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Code summarization aims to automatically generate functionality descriptions of code snippets. Faithful metrics are needed to measure to which degree the machine generated … |
JUANJUAN SHEN et. al. | 2021 IEEE 21st International Conference on Software … | 2021-12-01 |
616 | Sparse Is Enough in Scaling Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We study sparse variants for all layers in the Transformer and propose Scaling Transformers, a family of next generation Transformer models that use sparse layers to scale efficiently and perform unbatched decoding much faster than the standard Transformer as we scale up the model size. |
SEBASTIAN JASZCZUR et. al. | arxiv-cs.LG | 2021-11-24 |
617 | TWEETSUMM – A Dialog Summarization Dataset for Customer Service IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In a typical customer service chat scenario, customers contact a support center to ask for help or raise complaints, and human agents try to solve the issues. In most cases, at … |
G. FEIGENBLAT et. al. | ArXiv | 2021-11-23 |
618 | TWEETSUMM — A Dialog Summarization Dataset for Customer Service Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The goal of the present article is advancing the automation of this task. |
GUY FEIGENBLAT et. al. | arxiv-cs.CL | 2021-11-23 |
619 | Sparse Is Enough in Scaling Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We study sparse variants for all layers in the Transformer and propose Scaling Transformers, a family of next generation Transformer models that use sparse layers to scale efficiently and perform unbatched decoding much faster than the standard Transformer as we scale up the model size. |
SEBASTIAN JASZCZUR et. al. | nips | 2021-11-20 |
620 | R-Drop: Regularized Dropout for Neural Networks IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a simple consistency training strategy to regularize dropout, namely R-Drop, which forces the output distributions of different sub models generated by dropout to be consistent with each other. |
XIAOBO LIANG et. al. | nips | 2021-11-20 |
621 | Global-aware Beam Search for Neural Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study develops a calibrated beam-based algorithm with awareness of the global attention distribution for neural abstractive summarization, aiming to improve the local optimality problem of the original beam search in a rigorous way. |
Ye Ma; Zixun Lan; Lu Zong; Kaizhu Huang; | nips | 2021-11-20 |
622 | BARTScore: Evaluating Generated Text As Text Generation IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we conceptualize the evaluation of generated text as a text generation problem, modeled using pre-trained sequence-to-sequence models. |
Weizhe Yuan; Graham Neubig; Pengfei Liu; | nips | 2021-11-20 |
623 | Pointer Over Attention: An Improved Bangla Text Summarization Approach Using Hybrid Pointer Generator Network Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a hybrid pointer generator network to solve the shortcomings of reproducing factual details inadequately and phrase repetition. |
Nobel Dhar; Gaurob Saha; Prithwiraj Bhattacharjee; Avi Mallick; Md Saiful Islam; | arxiv-cs.CL | 2021-11-19 |
624 | Meeting Summarization with Pre-training and Clustering Methods Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we experiment with different approaches to improve the performance of query-based meeting summarization. |
Andras Huebner; Wei Ji; Xiang Xiao; | arxiv-cs.CL | 2021-11-15 |
625 | Incorporating Question Answering-Based Signals Into Abstractive Summarization Via Salient Span Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a method for incorporating question-answering (QA) signals into a summarization model. |
Daniel Deutsch; Dan Roth; | arxiv-cs.CL | 2021-11-15 |
626 | Efficient GAN-based Method for Extractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Background and Objectives: Text summarization plays an essential role in reducing time and cost in many domains such as medicine, engineering, etc. On the other hand, manual … |
Seyed Vahid Moravvej; M. J. M. Kahaki; M. S. Sartakhti; Mehdi Joodaki; | 2021-11-14 | |
627 | Q2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues Via Question Generation and Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by recent work on evaluating factual consistency in abstractive summarization, we propose an automatic evaluation metric for factual consistency in knowledge-grounded dialogue using automatic question generation and question answering. |
OR HONOVICH et. al. | emnlp | 2021-11-05 |
628 | MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we improve multilingual text-to-text transfer Transformer with translation pairs (mT6). |
ZEWEN CHI et. al. | emnlp | 2021-11-05 |
629 | Decision-Focused Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel problem, decision-focused summarization, where the goal is to summarize relevant information for a decision. |
Chao-Chun Hsu; Chenhao Tan; | emnlp | 2021-11-05 |
630 | HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To mitigate these issues, this paper proposes HetFormer, a Transformer-based pre-trained model with multi-granularity sparse attentions for long-text extractive summarization. |
YE LIU et. al. | emnlp | 2021-11-05 |
631 | Considering Nested Tree Structure in Sentence Extractive Summarization with Pre-trained Transformer IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a nested tree-based extractive summarization model on RoBERTa (NeRoBERTa), where nested tree structures consist of syntactic and discourse trees in a given document. |
Jingun Kwon; Naoki Kobayashi; Hidetaka Kamigaito; Manabu Okumura; | emnlp | 2021-11-05 |
632 | Gradient-Based Adversarial Factual Consistency Evaluation for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we proposed an efficient weak-supervised adversarial data augmentation approach to form the factual consistency dataset. |
Zhiyuan Zeng; Jiaze Chen; Weiran Xu; Lei Li; | emnlp | 2021-11-05 |
633 | Learn to Copy from The Copying History: Correlational Copy Network for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel copying scheme named Correlational Copying Network (CoCoNet) that enhances the standard copying mechanism by keeping track of the copying history. |
HAORAN LI et. al. | emnlp | 2021-11-05 |
634 | Fine-grained Factual Consistency Assessment for Abstractive Summarization Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a fine-grained two-stage Fact Consistency assessment framework for Summarization models (SumFC). |
Sen Zhang; Jianwei Niu; Chuyuan Wei; | emnlp | 2021-11-05 |
635 | AUTOSUMM: Automatic Model Creation for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose methods to automatically create deep learning models for the tasks of extractive and abstractive text summarization. |
SHARMILA REDDY NANGI et. al. | emnlp | 2021-11-05 |
636 | Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Modified encoder architectures such as LED or LoBART use local attention patterns to address this problem for summarization. In contrast, this work focuses on the transformer’s encoder-decoder attention mechanism. |
Potsawee Manakul; Mark Gales; | emnlp | 2021-11-05 |
637 | Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a unifying perspective based on the nature of information change in NLG tasks, including compression (e.g., summarization), transduction (e.g., text rewriting), and creation (e.g., dialog). |
Mingkai Deng; Bowen Tan; Zhengzhong Liu; Eric Xing; Zhiting Hu; | emnlp | 2021-11-05 |
638 | Multiplex Graph Neural Network for Extractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address these problems, we propose a novel Multiplex Graph Convolutional Network (Multi-GCN) to jointly model different types of relationships among sentences and words. |
Baoyu Jing; Zeyu You; Tao Yang; Wei Fan; Hanghang Tong; | emnlp | 2021-11-05 |
639 | ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose ARMAN, a Transformer-based encoder-decoder model pre-trained with three novel objectives to address this issue. |
Alireza Salemi; Emad Kebriaei; Ghazal Neisi Minaei; Azadeh Shakery; | emnlp | 2021-11-05 |
640 | Frame Semantic-Enhanced Sentence Modeling for Sentence-level Extractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Frame Semantic-Enhanced Sentence Modeling for Extractive Summarization, which leverages Frame semantics to model sentences from both intra-sentence level and inter-sentence level, facilitating the text summarization task. |
Yong Guan; Shaoru Guo; Ru Li; Xiaoli Li; Hongye Tan; | emnlp | 2021-11-05 |
641 | StreamHover: Livestream Transcript Summarization and Annotation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present StreamHover, a framework for annotating and summarizing livestream transcripts. |
SANGWOO CHO et. al. | emnlp | 2021-11-05 |
642 | GupShup: Summarizing Open-Domain Code-Switched Conversations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Towards this objective, we introduce the task of abstractive summarization of Hindi-English (Hi-En) code-switched conversations. |
LAIBA MEHNAZ et. al. | emnlp | 2021-11-05 |
643 | Weakly Supervised Discourse Segmentation for Multiparty Oral Conversations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop a weak supervision approach to adapt, using minimal annotation, a state of the art discourse segmenter trained on written text to French conversation transcripts. |
Lila Gravellier; Julie Hunter; Philippe Muller; Thomas Pellegrini; Isabelle Ferran?; | emnlp | 2021-11-05 |
644 | Event Graph Based Sentence Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore the effective sentence fusion method in the context of text summarization. |
Ruifeng Yuan; Zili Wang; Wenjie Li; | emnlp | 2021-11-05 |
645 | Effective Sequence-to-Sequence Dialogue State Tracking IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we study this problem from the perspectives of pre-training objectives as well as the formats of context representations. |
Jeffrey Zhao; Mahdis Mahdieh; Ye Zhang; Yuan Cao; Yonghui Wu; | emnlp | 2021-11-05 |
646 | Improving Sequence-to-Sequence Pre-training Via Sequence Span Rewriting IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Sequence Span Rewriting (SSR), a self-supervised task for sequence-to-sequence (Seq2Seq) pre-training. |
Wangchunshu Zhou; Tao Ge; Canwen Xu; Ke Xu; Furu Wei; | emnlp | 2021-11-05 |
647 | Enriching and Controlling Global Semantics for Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we attempt to address this issue by introducing a neural topic model empowered with normalizing flow to capture the global semantics of the document, which are then integrated into the summarization model. |
Thong Nguyen; Anh Tuan Luu; Truc Lu; Tho Quan; | emnlp | 2021-11-05 |
648 | Automatic Text Evaluation Through The Lens of Wasserstein Barycenters IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: A new metric BaryScore to evaluate text generation based on deep contextualized embeddings (e.g., BERT, Roberta, ELMo) is introduced. |
Pierre Colombo; Guillaume Staerman; Chlo? Clavel; Pablo Piantanida; | emnlp | 2021-11-05 |
649 | Vision Guided Generative Pre-trained Language Models for Multimodal Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a simple yet effective method to construct vision guided (VG) GPLMs for the MAS task using attention-based add-on layers to incorporate visual information while maintaining their original text generation ability. |
Tiezheng Yu; Wenliang Dai; Zihan Liu; Pascale Fung; | emnlp | 2021-11-05 |
650 | Integrating Semantic Scenario and Word Relations for Abstractive Sentence Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To simultaneously capture the word relations and structure information from sentences, we propose a novel Dual Graph network for Abstractive Sentence Summarization. |
Yong Guan; Shaoru Guo; Ru Li; Xiaoli Li; Hu Zhang; | emnlp | 2021-11-05 |
651 | CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We study generating abstractive summaries that are faithful and factually consistent with the given articles. |
Shuyang Cao; Lu Wang; | emnlp | 2021-11-05 |
652 | Simple Conversational Data Augmentation for Semi-supervised Abstractive Dialogue Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To reduce the dependence on labeled summaries, in this work, we present a simple yet effective set of Conversational Data Augmentation (CODA) methods for semi-supervised abstractive conversation summarization, such as random swapping/deletion to perturb the discourse relations inside conversations, dialogue-acts-guided insertion to interrupt the development of conversations, and conditional-generation-based substitution to substitute utterances with their paraphrases generated based on the conversation context. |
Jiaao Chen; Diyi Yang; | emnlp | 2021-11-05 |
653 | Query-Based Summarization Using Reinforcement Learning and Transformer Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Query-based summarization is an interesting problem in the text summarization field. The reinforcement learning technique is popular for robotics and become accessible for the … |
Yllias Chali; Asif Mahmud; | 2021 IEEE 33rd International Conference on Tools with … | 2021-11-01 |
654 | Automatic Key Phrase Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The ever-increasing number of text articles on the internet necessitates automated key phrase tagging. Information retrieval is aided by automatic key phrase generation in … |
D. Zakrzewska; K. Mataśka; | 2021 International Conference on Engineering and Emerging … | 2021-10-27 |
655 | S2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a sequence-to-sequence fine-tuning toolkit s2s-ft, which adopts pretrained Transformers for conditional generation tasks. |
Hangbo Bao; Li Dong; Wenhui Wang; Nan Yang; Furu Wei; | arxiv-cs.CL | 2021-10-26 |
656 | Generating GitHub Repository Descriptions: A Comparison of Manual and Automated Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we examine the current practice of writing GitHub repository descriptions. |
Jazlyn Hellman; Eunbee Jang; Christoph Treude; Chenzhun Huang; Jin L. C. Guo; | arxiv-cs.SE | 2021-10-25 |
657 | Research on Automatic News Text Summarization Technology Based on GPT2 Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization helps human beings to read news in fragmented time, realize the news from long to short, and get important information quickly, accurately and … |
Zhenmin Yang; Yonghao Dong; Jiange Deng; Baocheng Sha; Tao Xu; | 2021 3rd International Conference on Artificial … | 2021-10-23 |
658 | Overview of The 2021 Key Point Analysis Shared Task IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We describe the 2021 Key Point Analysis (KPA-2021) shared task on key point analysis that we organized as a part of the 8th Workshop on Argument Mining (ArgMining 2021) at EMNLP 2021. |
RONI FRIEDMAN et. al. | arxiv-cs.CL | 2021-10-20 |
659 | CNewSum: A Large-scale Chinese News Summarization Dataset with Human-annotated Adequacy and Deducibility Level Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a large-scale Chinese news summarization dataset CNewSum, which consists of 304,307 documents and human-written summaries for the news feed. We examine recent methods on CNewSum and release our dataset to provide a solid testbed for automatic Chinese summarization research. |
Danqing Wang; Jiaze Chen; Xianze Wu; Hao Zhou; Lei Li; | arxiv-cs.CL | 2021-10-20 |
660 | CLASS: A Novel Method for Chinese Legal Judgments Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose a novel method to generate abstractive summarization of Chinese legal judgments named CLASS (Chinese LegAl judgmentS Summarization) which exploits the element structure … |
Dongjin Li; Ke Yang; Lijun Zhang; Dawei Yin; Dezhong Peng; | Proceedings of the 5th International Conference on Computer … | 2021-10-19 |
661 | Summ^N: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Summ$^N$, a simple, flexible, and effective multi-stage framework for input texts that are longer than the maximum context length of typical pretrained LMs. |
YUSEN ZHANG et. al. | arxiv-cs.CL | 2021-10-16 |
662 | Towards Making The Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper demonstrates that multilingual pretraining and multilingual fine-tuning are both critical for facilitating cross-lingual transfer in zero-shot translation, where the neural machine translation (NMT) model is tested on source languages unseen during supervised training. Following this idea, we present SixT+, a strong many-to-English NMT model that supports 100 source languages but is trained with a parallel dataset in only six source languages. |
GUANHUA CHEN et. al. | arxiv-cs.CL | 2021-10-16 |
663 | Training Dynamics for Text Summarization Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we analyze the training dynamics for generation models, focusing on summarization. |
Tanya Goyal; Jiacheng Xu; Junyi Jessy Li; Greg Durrett; | arxiv-cs.CL | 2021-10-15 |
664 | MReD: A Meta-Review Dataset for Structure-Controllable Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present experimental results on start-of-the-art summarization models, and propose methods for structure-controlled generation with both extractive and abstractive models using our annotated data. |
CHENHUI SHEN et. al. | arxiv-cs.CL | 2021-10-14 |
665 | CaPE: Contrastive Parameter Ensembling for Reducing Hallucination in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a new method called Contrastive Parameter Ensembling (CaPE) to use training data more effectively, utilizing variations in noise in training samples to reduce hallucination. |
PRAFULLA KUMAR CHOUBEY et. al. | arxiv-cs.CL | 2021-10-14 |
666 | Modeling Endorsement for Multi-Document Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we model the cross-document endorsement effect and its utilization in multiple document summarization. |
Logan Lebanoff; Bingqing Wang; Zhe Feng; Fei Liu; | arxiv-cs.CL | 2021-10-14 |
667 | Speech Summarization Using Restricted Self-Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a single model optimized end-to-end for speech summarization. |
Roshan Sharma; Shruti Palaskar; Alan W Black; Florian Metze; | arxiv-cs.CL | 2021-10-12 |
668 | HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To mitigate these issues, this paper proposes HETFORMER, a Transformer-based pre-trained model with multi-granularity sparse attentions for long-text extractive summarization. |
YE LIU et. al. | arxiv-cs.CL | 2021-10-12 |
669 | Enhance Long Text Understanding Via Distilled Gist Detector from Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we consider the problem of how to disentangle the gist-relevant and irrelevant information for long text understanding. |
Yan Liu; Yazheng Yang; | arxiv-cs.CL | 2021-10-10 |
670 | Automatic Text Extractive Summarization Based on Graph and Pre-trained Language Model Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, an attention matrix between the sentences of the whole text is adopted as a weighted adjacent matrix of a fully connected graph of the text, which can be produced through the pre-training language model. |
Yuan-Ching Lin; Jinwen Ma; | arxiv-cs.CL | 2021-10-10 |
671 | Bayesian Active Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Bayesian Active Summarization (BAS), as a method of combining active learning methods with state-of-the-art summarization models. |
Alexios Gidiotis; Grigorios Tsoumakas; | arxiv-cs.CL | 2021-10-09 |
672 | HydraSum: Disentangling Stylistic Features in Text Summarization Using Multi-Decoder Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these are implicitly encoded within model parameters and specific styles cannot be enforced. To address this, we introduce HydraSum, a new summarization architecture that extends the single decoder framework of current models to a mixture-of-experts version with multiple decoders. |
Tanya Goyal; Nazneen Fatema Rajani; Wenhao Liu; Wojciech Kryściński; | arxiv-cs.CL | 2021-10-08 |
673 | VieSum: How Robust Are Transformer-based Models on Vietnamese Summarization? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the robustness of transformer-based encoder-decoder architectures for Vietnamese abstractive summarization. |
Hieu Nguyen; Long Phan; James Anibal; Alec Peltekian; Hieu Tran; | arxiv-cs.CL | 2021-10-08 |
674 | Noisy Text Data: Achilles’ Heel of Popular Transformer Based NLP Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We address the open question by Kumar et al. (2020) to explore the sensitivity of popular transformer based NLP models to noise in the text data. |
Kartikay Bagla; Ankit Kumar; Shivam Gupta; Anuj Gupta; | arxiv-cs.CL | 2021-10-07 |
675 | HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow Articles Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present HowSumm, a novel large-scale dataset for the task of query-focused multi-document summarization (qMDS), which targets the use-case of generating actionable instructions from a set of sources. |
ODELLIA BONI et. al. | arxiv-cs.CL | 2021-10-07 |
676 | Key Point Analysis Via Contrastive Learning and Extractive Argument Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents our proposed approach to the Key Point Analysis shared task, collocated with the 8th Workshop on Argument Mining. |
MILAD ALSHOMARY et. al. | arxiv-cs.CL | 2021-09-30 |
677 | Privacy Policy Question Answering Assistant: A Query-Guided Extractive Summarization Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To facilitate a more personalized interaction with the policies, in this work, we propose an automated privacy policy question answering assistant that extracts a summary in response to the input user query. |
Moniba Keymanesh; Micha Elsner; Srinivasan Parthasarathy; | arxiv-cs.CL | 2021-09-29 |
678 | Who Speaks Like A Style of Vitamin: Towards Syntax-Aware DialogueSummarization Using Multi-task Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, we constructed a syntax-aware model by leveraging linguistic information (i.e., POS tagging), which alleviates the above issues by inherently distinguishing sentences uttered from individual speakers. |
Seolhwa Lee; Kisu Yang; Chanjun Park; João Sedoc; Heuiseok Lim; | arxiv-cs.CL | 2021-09-29 |
679 | Who Speaks Like A Style of Vitamin: Towards Syntax-Aware Dialogue Summarization Using Multi-task Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive dialogue summarization is a challenging task for several reasons. First, most of the important pieces of information in a conversation are scattered across utterances … |
Seolhwa Lee; Kisu Yang; Chanjun Park; João Sedoc; Heuiseok Lim; | IEEE Access | 2021-09-29 |
680 | Investigating Entropy for Extractive Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we employ Shannon entropy to capture informativeness of sentences. |
Alka Khurana; Vasudha Bhatnagar; | arxiv-cs.IR | 2021-09-22 |
681 | Recursively Summarizing Books with Human Feedback IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present progress on this problem on the task of abstractive summarization of entire fiction novels. We release datasets of samples from our model. |
JEFF WU et. al. | arxiv-cs.CL | 2021-09-22 |
682 | BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present BARTpho with two versions, BARTpho-syllable and BARTpho-word, which are the first public large-scale monolingual sequence-to-sequence models pre-trained for Vietnamese. |
Nguyen Luong Tran; Duong Minh Le; Dat Quoc Nguyen; | arxiv-cs.CL | 2021-09-20 |
683 | Exploring Multitask Learning for Low-Resource AbstractiveSummarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the effect of using multitask learning for abstractive summarization in the context of small training corpora. |
Ahmed Magooda; Mohamed Elaraby; Diane Litman; | arxiv-cs.CL | 2021-09-17 |
684 | Mitigating Data Scarceness Through Data Synthesis, Augmentation and Curriculum for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a method of data synthesis with paraphrasing, a data augmentation technique with sample mixing, and curriculum learning with two new difficulty metrics based on specificity and abstractiveness. |
Ahmed Magooda; Diane Litman; | arxiv-cs.CL | 2021-09-17 |
685 | RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose RetrievalSum, a novel retrieval enhanced abstractive summarization framework consisting of a dense Retriever and a Summarizer. |
Chenxin An; Ming Zhong; Zhichao Geng; Jianqiang Yang; Xipeng Qiu; | arxiv-cs.CL | 2021-09-16 |
686 | Augmented Abstractive Summarization With Document-LevelSemantic Graph Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous abstractive methods apply sequence-to-sequence structures to generate summary without a module to assist the system to detect vital mentions and relationships within a document. |
Qiwei Bi; Haoyuan Li; Kun Lu; Hanfang Yang; | arxiv-cs.CL | 2021-09-13 |
687 | Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a unifying perspective that facilitates the design of metrics for a wide range of language generation tasks and quality aspects. |
Mingkai Deng; Bowen Tan; Zhengzhong Liu; Eric P. Xing; Zhiting Hu; | arxiv-cs.CL | 2021-09-13 |
688 | UniMS: A Unified Framework for Multimodal Summarization with Knowledge Distillation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Besides, we introduce a visual guided decoder to better integrate textual and visual modalities in guiding abstractive text generation. |
ZHENGKUN ZHANG et. al. | arxiv-cs.CL | 2021-09-13 |
689 | Does Pretraining for Summarization Require Knowledge Transfer? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we challenge the knowledge transfer story, showing that pretraining on documents consisting of character n-grams selected at random, we can nearly match the performance of models pretrained on real corpora. |
Kundan Krishna; Jeffrey Bigham; Zachary C. Lipton; | arxiv-cs.CL | 2021-09-10 |
690 | Sparsity and Sentence Structure in Encoder-Decoder Attention of Summarization Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Transformer models have achieved state-of-the-art results in a wide range of NLP tasks including summarization. |
Potsawee Manakul; Mark J. F. Gales; | arxiv-cs.CL | 2021-09-08 |
691 | A Deep Neural Architecture for Decision-Aware Meta-Review Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatically generating meta-reviews from peer-reviews is a new and challenging task. Although close, the task is not precisely summarizing the peer-reviews. Usually, a … |
Asheesh Kumar; Tirthankar Ghosal; Asif Ekbal; | 2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) | 2021-09-01 |
692 | Monolingual Versus Multilingual BERTology for Vietnamese Extractive Multi-Document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we showcase how BERT can be implemented for extractive text summarization in Vietnamese on multi-document. |
Huy Quoc To; Kiet Van Nguyen; Ngan Luu-Thuy Nguyen; Anh Gia-Tuan Nguyen; | arxiv-cs.CL | 2021-08-31 |
693 | Hallucinated But Factual! Inspecting The Factuality of Hallucinations in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel detection approach that separates factual from non-factual hallucinations of entities. |
Meng Cao; Yue Dong; Jackie Chi Kit Cheung; | arxiv-cs.CL | 2021-08-30 |
694 | Factual Consistency Evaluation for Text Summarization Via Counterfactual Estimation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In light of these challenges, we propose a novel metric to evaluate the factual consistency in text summarization via counterfactual estimation, which formulates the causal relationship among the source document, the generated summary, and the language prior. |
Yuexiang Xie; Fei Sun; Yang Deng; Yaliang Li; Bolin Ding; | arxiv-cs.CL | 2021-08-30 |
695 | SummerTime: Text Summarization Toolkit for Non-experts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent advances in summarization provide models that can generate summaries of higher quality. |
ANSONG NI et. al. | arxiv-cs.CL | 2021-08-28 |
696 | Automatic Text Evaluation Through The Lens of Wasserstein Barycenters IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: By modelling the layer output of deep contextualized embeddings as a probability distribution rather than by a vector embedding; this framework provides a natural way to aggregate the different outputs through the Wasserstein space topology. |
Pierre Colombo; Guillaume Staerman; Chloe Clavel; Pablo Piantanida; | arxiv-cs.CL | 2021-08-27 |
697 | Alleviating Exposure Bias Via Contrastive Learning for Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To remedy this problem, we propose to leverage contrastive learning to decrease the likelihood of these low-quality summaries, and meanwhile increase the likelihood of the gold summary. |
Shichao Sun; Wenjie Li; | arxiv-cs.CL | 2021-08-26 |
698 | Enhanced Seq2Seq Autoencoder Via Contrastive Learning for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a denoising sequence-to-sequence (seq2seq) autoencoder via contrastive learning for abstractive text summarization. |
Chujie Zheng; Kunpeng Zhang; Harry Jiannan Wang; Ling Fan; Zhe Wang; | arxiv-cs.CL | 2021-08-26 |
699 | Audio Summarization for Podcasts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose a novel system to automatically generate audio summaries for podcasts, allowing listeners to quickly preview podcast episodes. The proposed system first transcribes the … |
Aneesh Vartakavi; Amanmeet Garg; Z. Rafii; | 2021 29th European Signal Processing Conference (EUSIPCO) | 2021-08-23 |
700 | Hierarchical Summarization for Longform Spoken Dialog IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Consequently, we design a two stage ASR and text summarization pipeline and propose a set of semantic segmentation and merging algorithms to resolve these speech modeling challenges. |
Daniel Li; Thomas Chen; Albert Tung; Lydia Chilton; | arxiv-cs.CL | 2021-08-21 |
701 | MTG: A Benchmark Suite for Multilingual Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce MTG, a new benchmark suite for training and evaluating multilingual text generation. |
YIRAN CHEN et. al. | arxiv-cs.CL | 2021-08-13 |
702 | MTG: A Benchmarking Suite for Multilingual Text Generation IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We introduce MTG, a new benchmark suite for training and evaluating multilingual text generation. It is the first-proposed multilingual multiway text generation dataset with the … |
YIRAN CHEN et. al. | NAACL-HLT | 2021-08-13 |
703 | ICAF: Iterative Contrastive Alignment Framework for Multimodal Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, missing awareness of cross-modal matching from many frameworks leads to performance reduction. To solve these two drawbacks, we propose an Iterative Contrastive Alignment Framework (ICAF) that uses recurrent alignment and contrast to capture the coherences between images and texts. |
ZIJIAN ZHANG et. al. | arxiv-cs.AI | 2021-08-11 |
704 | Controllable Summarization with Constrained Markov Decision Process IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel training framework based on Constrained Markov Decision Process (CMDP), which conveniently includes a reward function along with a set of constraints, to facilitate better summarization control. |
Hou Pong Chan; Lu Wang; Irwin King; | arxiv-cs.CL | 2021-08-07 |
705 | Fine-tuning GPT-3 for Russian Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aim to showcase ruGPT3 ability to summarize texts, fine-tuning it on the corpora of Russian news with their corresponding human-generated summaries. |
Alexandr Nikolich; Arina Puchkova; | arxiv-cs.CL | 2021-08-07 |
706 | Evaluating The Tradeoff Between Abstractiveness and Factuality in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we analyze the tradeoff between abstractiveness and factuality of generated summaries across multiple datasets and models, using extensive human evaluations of factuality. |
Markus Dreyer; Mengwen Liu; Feng Nan; Sandeep Atluri; Sujith Ravi; | arxiv-cs.CL | 2021-08-05 |
707 | Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, most research conducted in the field of abstractive text summarization focuses on neural-based models alone, without considering their combination with knowledge-based … |
P. Kouris; Georgios Alexandridis; A. Stafylopatis; | Computational Linguistics | 2021-08-05 |
708 | Summary Explorer: Visualizing The State of The Art in Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces Summary Explorer, a new tool to support the manual inspection of text summarization systems by compiling the outputs of 55~state-of-the-art single document summarization approaches on three benchmark datasets, and visually exploring them during a qualitative assessment. |
Shahbaz Syed; Tariq Yousef; Khalid Al-Khatib; Stefan Jänicke; Martin Potthast; | arxiv-cs.CL | 2021-08-04 |
709 | EmailSum: Abstractive Email Thread Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Such summaries help analysis of the long text to quickly catch up with the decisions made and thus improve our work or communication efficiency. |
Shiyue Zhang; Asli Celikyilmaz; Jianfeng Gao; Mohit Bansal; | arxiv-cs.CL | 2021-07-30 |
710 | Deep Differential Amplifier for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we conceptualize the single-document extractive summarization as a rebalance problem and present a deep differential amplifier framework. |
RUIPENG JIA et. al. | acl | 2021-07-26 |
711 | Dissecting Generation Modes for Abstractive Summarization Models Via Ablation and Attribution IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a two-step method to interpret summarization model decisions. |
Jiacheng Xu; Greg Durrett; | acl | 2021-07-26 |
712 | POS-Constrained Parallel Decoding for Non-autoregressive Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To provide a feasible solution to the multimodality problem of NAG, we propose incorporating linguistic structure (Part-of-Speech sequence in particular) into NAG inference instead of relying on teacher AG. |
Kexin Yang; Wenqiang Lei; Dayiheng Liu; Weizhen Qi; Jiancheng Lv; | acl | 2021-07-26 |
713 | SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a conceptually simple while empirically powerful framework for abstractive summarization, SimCLS, which can bridge the gap between the learning objective and evaluation metrics resulting from the currently dominated sequence-to-sequence learning framework by formulating text generation as a reference-free evaluation problem (i.e., quality estimation) assisted by contrastive learning. |
Yixin Liu; Pengfei Liu; | acl | 2021-07-26 |
714 | Video Paragraph Captioning As A Text Summarization Task IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel framework by taking this task as a text summarization task. |
Hui Liu; Xiaojun Wan; | acl | 2021-07-26 |
715 | Unsupervised Extractive Summarization-Based Representations for Accurate and Explainable Collaborative Filtering IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We pioneer the first extractive summarization-based collaborative filtering model called ESCOFILT. |
Reinald Adrian Pugoy; Hung-Yu Kao; | acl | 2021-07-26 |
716 | CLIP: A Dataset for Extracting Action Items for Physicians from Hospital Discharge Notes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we describe our creation of a dataset of clinical action items annotated over MIMIC-III, the largest publicly available dataset of real clinical notes. |
JAMES MULLENBACH et. al. | acl | 2021-07-26 |
717 | End-to-End AMR Corefencence Resolution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce the first end-to-end AMR coreference resolution model in order to build multi-sentence AMRs. |
Qiankun Fu; Linfeng Song; Wenyu Du; Yue Zhang; | acl | 2021-07-26 |
718 | Long-Span Summarization Via Local Attention and Content Selection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we exploit large pre-trained transformer-based models and address long-span dependencies in abstractive summarization using two methods: local self-attention; and explicit content selection. |
Potsawee Manakul; Mark Gales; | acl | 2021-07-26 |
719 | BASS: Boosting Abstractive Summarization with Unified Semantic Graph IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present BASS, a novel framework for Boosting Abstractive Summarization based on a unified Semantic graph, which aggregates co-referent phrases distributing across a long range of context and conveys rich relations between phrases. |
WENHAO WU et. al. | acl | 2021-07-26 |
720 | ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this gap, we design annotation protocols motivated by an issues-viewpoints-assertions framework to crowdsource four new datasets on diverse online conversation forms of news comments, discussion forums, community question answering forums, and email threads. |
ALEXANDER FABBRI et. al. | acl | 2021-07-26 |
721 | Cross-Lingual Abstractive Summarization with Limited Parallel Resources IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To bridge these connections, we propose a novel Multi-Task framework for Cross-Lingual Abstractive Summarization (MCLAS) in a low-resource setting. |
Yu Bai; Yang Gao; Heyan Huang; | acl | 2021-07-26 |
722 | Improving Factual Consistency of Abstractive Summarization Via Question Answering IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we present an approach to address factual consistency in summarization. |
FENG NAN et. al. | acl | 2021-07-26 |
723 | Self-Supervised Multimodal Opinion Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To use the abundant information contained in non-text data, we propose a self-supervised multimodal opinion summarization framework called MultimodalSum. |
Jinbae Im; Moonki Kim; Hoyeop Lee; Hyunsouk Cho; Sehee Chung; | acl | 2021-07-26 |
724 | DeepTitle — Leveraging BERT to Generate Search Engine Optimized Headlines Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we showcase how a pre-trained language model can be leveraged to create an abstractive news headline generator for German language. |
CRISTIAN ANASTASIU et. al. | arxiv-cs.LG | 2021-07-22 |
725 | MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce MemSum (Multi-step Episodic Markov decision process extractive SUMmarizer), a reinforcement-learning-based extractive summarizer enriched at each step with information on the current extraction history. |
Nianlong Gu; Elliott Ash; Richard H. R. Hahnloser; | arxiv-cs.CL | 2021-07-19 |
726 | Abstractive Text Summarization with Hierarchical Multi-scale Abstraction Modeling and Dynamic Memory Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel abstractive text summarization method with hierarchical multi-scale abstraction modeling and dynamic memory (called MADY). |
Lihan Wang; Min Yang; Chengming Li; Ying Shen; Ruifeng Xu; | sigir | 2021-07-13 |
727 | Self-Supervised Contrastive Learning for Code Retrieval and Summarization Via Semantic-Preserving Transformations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Corder, a self-supervised contrastive learning framework for source code model. |
Nghi D. Q. Bui; Yijun Yu; Lingxiao Jiang; | sigir | 2021-07-13 |
728 | Distant Supervision Based Machine Reading Comprehension for Extractive Summarization in Customer Service Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to solve the above challenges, we propose a Distant Supervision based Machine Reading Comprehension model for extractive Summarization (DSMRC-S). |
BING MA et. al. | sigir | 2021-07-13 |
729 | DepressionNet: Learning Multi-modalities with User Post Summarization for Depression Detection on Social Media IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To overcome the shortcomings in the existing automatic depression detection methods, we propose a novel computational framework for automatic depression detection that initially selects relevant content through a hybrid extractive and abstractive summarization strategy on the sequence of all user tweets leading to a more fine-grained and relevant content. |
Hamad Zogan; Imran Razzak; Shoaib Jameel; Guandong Xu; | sigir | 2021-07-13 |
730 | Unsupervised Extractive Text Summarization with Distance-Augmented Sentence Graphs IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an unsupervised approach to extractive text summarization, which uses an automatically constructed sentence graph from each document to select salient sentences for summarization based on both the similarities and relative distances in the neighborhood of each sentences. |
Jingzhou Liu; Dominic J. D. Hughes; Yiming Yang; | sigir | 2021-07-13 |
731 | Chatbot : A Question Answering System for Student Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the last few years there has been a fast growing up of the use of Chatbots in various fields, such as Customer Service, Marketing, Educational, Health Care and many others. … |
Li En Chen; Shein-Yung Cheng; J. Heh; | 2021 International Conference on Advanced Learning … | 2021-07-01 |
732 | Improving Factual Consistency of Abstractive Summarization on Customer Feedback Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a set of methods to enhance the factual consistency of abstractive summarization on customer feedback. |
Yang Liu; Yifei Sun; Vincent Gao; | arxiv-cs.CL | 2021-06-30 |
733 | Incorporating Domain Knowledge for Extractive Summarization of Legal Case Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this gap, we propose an unsupervised summarization algorithm DELSumm which is designed to systematically incorporate guidelines from legal experts into an optimization setup. |
Paheli Bhattacharya; Soham Poddar; Koustav Rudra; Kripabandhu Ghosh; Saptarshi Ghosh; | arxiv-cs.CL | 2021-06-30 |
734 | Topic Modeling Based Extractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel method to summarize a text document by clustering its contents based on latent topics produced using topic modeling techniques and by generating extractive summaries for each of the identified text clusters. |
Kalliath Abdul Rasheed Issam; Shivam Patel; Subalalitha C. N; | arxiv-cs.CL | 2021-06-29 |
735 | Dialect Diversity in Text Summarization on Twitter IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To correct for the dialect bias, we employ a framework that takes an existing text summarization algorithm as a blackbox and, using a small set of dialect-diverse sentences, returns a summary that is relatively more dialect-diverse. |
Vijay Keswani; L. Elisa Celis; | www | 2021-06-25 |
736 | XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present XL-Sum, a comprehensive and diverse dataset comprising 1 million professionally annotated article-summary pairs from BBC, extracted using a set of carefully designed heuristics. We are releasing our dataset and models to encourage future research on multilingual abstractive summarization. |
TAHMID HASAN et. al. | arxiv-cs.CL | 2021-06-25 |
737 | DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation By Augmenting Pretrained Multilingual Encoders IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To reduce this gap, we introduce DeltaLM, a pretrained multilingual encoder-decoder model that regards the decoder as the task layer of off-the-shelf pretrained encoders. |
SHUMING MA et. al. | arxiv-cs.CL | 2021-06-25 |
738 | Keyword-aware Abstractive Summarization By Extracting Set-level Intermediate Summaries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a extractor-abstractor framework in which the keyword-based extractor selects a few sets of salient sentences from the input document and then the abstractor paraphrases these sets of sentences in parallel, which are more aligned to the summary, to generate the final summary. |
Yizhu Liu; Qi Jia; Kenny Zhu; | www | 2021-06-25 |
739 | Extractive Approach for Text Summarisation Using Graphs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our paper explores different graph-related algorithms that can be used in solving the text summarization problem using an extractive approach. |
Kastriot Kadriu; Milenko Obradovic; | arxiv-cs.CL | 2021-06-21 |
740 | A Condense-then-Select Strategy for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this limitation, we propose a novel condense-then-select framework for text summarization. |
Hou Pong Chan; Irwin King; | arxiv-cs.CL | 2021-06-19 |
741 | Subjective Bias in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper a lightweight and effective method to extract the feature embeddings of subjective styles is proposed. |
LEI LI et. al. | arxiv-cs.CL | 2021-06-18 |
742 | Unsupervised Abstractive Opinion Summarization By Generating Sentences with Tree-Structured Topic Guidance IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a novel unsupervised abstractive summarization method for opinionated texts. |
Masaru Isonuma; Junichiro Mori; Danushka Bollegala; Ichiro Sakata; | arxiv-cs.CL | 2021-06-15 |
743 | VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present VT-SSum, a benchmark dataset with spoken language for video transcript segmentation and summarization, which includes 125K transcript-summary pairs from 9,616 videos. |
Tengchao Lv; Lei Cui; Momcilo Vasilijevic; Furu Wei; | arxiv-cs.CL | 2021-06-10 |
744 | Neural Abstractive Unsupervised Summarization of Online News Discussions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We address this challenging task by introducing a novel method that generates abstractive summaries of online news discussions. |
Ignacio Tampe Palma; Marcelo Mendoza; Evangelos Milios; | arxiv-cs.CL | 2021-06-07 |
745 | Extractive Research Slide Generation Using Windowed Labeling Ranking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a method to automatically generate slides for scientific papers based on a corpus of 5000 paper-slide pairs compiled from conference proceedings websites. |
Athar Sefid; Jian Wu; Prasenjit Mitra; Lee Giles; | arxiv-cs.CL | 2021-06-06 |
746 | CLIP: A Dataset for Extracting Action Items for Physicians from Hospital Discharge Notes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we describe our creation of a dataset of clinical action items annotated over MIMIC-III, the largest publicly available dataset of real clinical notes. |
JAMES MULLENBACH et. al. | arxiv-cs.CL | 2021-06-04 |
747 | AgreeSum: Agreement-Oriented Multi-Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We aim to renew interest in a particular multi-document summarization (MDS) task which we call AgreeSum: agreement-oriented multi-document summarization. Given the lack of existing datasets, we create a dataset for AgreeSum, and provide annotations on article-summary entailment relations for a subset of the clusters in the dataset. |
Richard Yuanzhe Pang; Adam D. Lelkes; Vinh Q. Tran; Cong Yu; | arxiv-cs.CL | 2021-06-04 |
748 | To Point or Not to Point: Understanding How Abstractive Summarizers Paraphrase Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: But despite these improved metrics, there is limited understanding of the strategies different models employ, and how those strategies relate their understanding of language. |
Matt Wilber; William Timkey; Marten Van Schijndel; | arxiv-cs.CL | 2021-06-03 |
749 | Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we adapt TP-TRANSFORMER (Schlag et al., 2019), an architecture that enriches the original Transformer (Vaswani et al., 2017) with the explicitly compositional Tensor Product Representation (TPR), for the task of abstractive summarization. |
YICHEN JIANG et. al. | arxiv-cs.CL | 2021-06-02 |
750 | CoRank: A Clustering Cum Graph Ranking Approach for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This research work proposes CoRank, a two-stage sentence selection model involving clustering and then ranking of sentences. |
Mohd Khizir Siddiqui; Amreen Ahmad; Om Pal; Tanvir Ahmad; | arxiv-cs.SI | 2021-06-01 |
751 | LenAtten: An Effective Length Controlling Unit For Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present an effective length controlling unit Length Attention (LenAtten) to break this trade-off. |
ZHONGYI YU et. al. | arxiv-cs.CL | 2021-06-01 |
752 | ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this gap, we design annotation protocols motivated by an issues–viewpoints–assertions framework to crowdsource four new datasets on diverse online conversation forms of news comments, discussion forums, community question answering forums, and email threads. |
ALEXANDER R. FABBRI et. al. | arxiv-cs.CL | 2021-06-01 |
753 | Question-aware Transformer Models for Consumer Health Question Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study the task of abstractive summarization for real-world consumer health questions. |
Shweta Yadav; Deepak Gupta; Asma Ben Abacha; Dina Demner-Fushman; | arxiv-cs.CL | 2021-06-01 |
754 | Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning Based Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Therefore, in this paper, we present a thorough analysis of 75 BNLP research papers and categorize them into 11 categories, namely Information Extraction, Machine Translation, Named Entity Recognition, Parsing, Parts of Speech Tagging, Question Answering System, Sentiment Analysis, Spam and Fake Detection, Text Summarization, Word Sense Disambiguation, and Speech Processing and Recognition. |
OVISHAKE SEN et. al. | arxiv-cs.CL | 2021-05-31 |
755 | Corpus-Based Paraphrase Detection Experiments and Review IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we give a performance overview of various types of corpus-based models, especially deep learning (DL) models, with the task of paraphrase detection. |
Tedo Vrbanec; Ana Mestrovic; | arxiv-cs.CL | 2021-05-31 |
756 | Bangla Natural Language Processing: A Comprehensive Analysis of Classical, Machine Learning, and Deep Learning-Based Methods IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Bangla language is the seventh most spoken language, with 265 million native and non-native speakers worldwide. However, English is the predominant language for online … |
OVISHAKE SEN et. al. | IEEE Access | 2021-05-31 |
757 | Reinforced Generative Adversarial Network for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new architecture that combines reinforcement learning and adversarial generative networks to enhance the sequence-to-sequence attention model. |
Tianyang Xu; Chunyun Zhang; | arxiv-cs.CL | 2021-05-31 |
758 | Text Summarization with Latent Queries Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce LaQSum, the first unified text summarization system that learns Latent Queries from documents for abstractive summarization with any existing query forms. |
Yumo Xu; Mirella Lapata; | arxiv-cs.CL | 2021-05-31 |
759 | Noised Consistency Training for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we argue that this limitation can be overcome by a semi-supervised approach: consistency training which is to leverage large amounts of unlabeled data to improve the performance of supervised learning over a small corpus. |
JUNNAN LIU et. al. | arxiv-cs.CL | 2021-05-28 |
760 | Improve Query Focused Abstractive Summarization By Incorporating Answer Relevance IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose QFS-BART, a model that incorporates the explicit answer relevance of the source documents given the query via a question answering model, to generate coherent and answer-related summaries. |
Dan Su; Tiezheng Yu; Pascale Fung; | arxiv-cs.CL | 2021-05-27 |
761 | AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a study of domain adaptation for the abstractive summarization task across six diverse target domains in a low-resource setting. |
Tiezheng Yu; Zihan Liu; Pascale Fung; | naacl | 2021-05-23 |
762 | Annotating and Modeling Fine-grained Factuality in Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We explore both synthetic and human-labeled data sources for training models to identify factual errors in summarization, and study factuality at the word-, dependency-, and sentence-level. |
Tanya Goyal; Greg Durrett; | naacl | 2021-05-23 |
763 | Attention Head Masking for Inference Time Content Selection in Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a simple-yet-effective attention head masking technique, which is applied on encoder-decoder attentions to pinpoint salient content at inference time. |
Shuyang Cao; Lu Wang; | naacl | 2021-05-23 |
764 | D2S: Document-to-Slide Generation Via Query-Based Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we first contribute a new dataset, SciDuet, consisting of pairs of papers and their corresponding slides decks from recent years’ NLP and ML conferences (e.g., ACL). Secondly, we present D2S, a novel system that tackles the document-to-slides task with a two-step approach: |
Edward Sun; Yufang Hou; Dakuo Wang; Yunfeng Zhang; Nancy X. R. Wang; | naacl | 2021-05-23 |
765 | Mask Attention Networks: Rethinking and Strengthen Transformer IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a novel understanding of SAN and FFN as Mask Attention Networks (MANs) and show that they are two special cases of MANs with static mask matrices. |
ZHIHAO FAN et. al. | naacl | 2021-05-23 |
766 | Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a novel and generalizable method, called WikiTransfer, for fine-tuning pretrained models for summarization in an unsupervised, dataset-specific manner. |
ALEXANDER FABBRI et. al. | naacl | 2021-05-23 |
767 | Sliding Selector Network with Dynamic Memory for Extractive Summarization of Long Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this issue, we propose the sliding selector network with dynamic memory for extractive summarization of long-form documents, which employs a sliding window to extract summary sentences segment by segment. |
Peng Cui; Le Hu; | naacl | 2021-05-23 |
768 | Enhancing Factual Consistency of Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a fact-aware summarization model FASum to extract and integrate factual relations into the summary generation process via graph attention. We then design a factual corrector model FC to automatically correct factual errors from summaries generated by existing systems. |
CHENGUANG ZHU et. al. | naacl | 2021-05-23 |
769 | Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the issue, we study contrast candidate generation and selection as a model-agnostic post-processing technique to correct the extrinsic hallucinations (i.e. information not present in the source text) in unfaithful summaries. |
Sihao Chen; Fan Zhang; Kazoo Sone; Dan Roth; | naacl | 2021-05-23 |
770 | DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To overcome the shortcomings in the existing automatic depression detection methods, we propose a novel computational framework for automatic depression detection that initially selects relevant content through a hybrid extractive and abstractive summarization strategy on the sequence of all user tweets leading to a more fine-grained and relevant content. |
Hamad Zogan; Imran Razzak; Shoaib Jameel; Guandong Xu; | arxiv-cs.LG | 2021-05-23 |
771 | RefSum: Refactoring Neural Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we highlight several limitations of previous methods, which motivates us to present a new framework Refactor that provides a unified view of text summarization and summaries combination. |
Yixin Liu; Zi-Yi Dou; Pengfei Liu; | naacl | 2021-05-23 |
772 | GSum: A General Framework for Guided Neural Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a general and extensible guided summarization framework (GSum) that can effectively take different kinds of external guidance as input, and we perform experiments across several different varieties. |
Zi-Yi Dou; Pengfei Liu; Hiroaki Hayashi; Zhengbao Jiang; Graham Neubig; | naacl | 2021-05-23 |
773 | Looking Beyond Sentence-Level Natural Language Inference for Question Answering and Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we use the multiple-choice reading comprehension (MCRC) and checking factual correctness of textual summarization (CFCS) tasks to investigate potential reasons for this. |
ANSHUMAN MISHRA et. al. | naacl | 2021-05-23 |
774 | Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the notion of uncertainty in the context of modern abstractive summarization models, using the tools of Bayesian Deep Learning. |
Alexios Gidiotis; Grigorios Tsoumakas; | arxiv-cs.CL | 2021-05-21 |
775 | See, Hear, Read: Leveraging Multimodality with Guided Attention for Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce AVIATE, the first large-scale dataset for abstractive text summarization with videos of diverse duration, compiled from presentations in well-known academic conferences like NDSS, ICML, NeurIPS, etc. |
Yash Kumar Atri; Shraman Pramanick; Vikram Goyal; Tanmoy Chakraborty; | arxiv-cs.LG | 2021-05-20 |
776 | Optimizing Multidocument Summarization By Blending Reinforcement Learning Policies Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We consider extractive summarization within a cluster of related texts (multidocument summarization). Unlike single-document summarization, redundancy is particularly important … |
A. Su; Difei Su; John M.Mulvey; H. Poor; | IEEE Transactions on Artificial Intelligence | 2021-05-18 |
777 | BookSum: A Collection of Datasets for Long-form Narrative Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While relevant, such datasets will offer limited challenges for future generations of text summarization systems. We address these issues by introducing BookSum, a collection of datasets for long-form narrative summarization. |
Wojciech Kryściński; Nazneen Rajani; Divyansh Agarwal; Caiming Xiong; Dragomir Radev; | arxiv-cs.CL | 2021-05-17 |
778 | A Large-Scale Chinese Long-Text Extractive Summarization Corpus Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we publish a large-scale Chinese Long-text Extractive Summarization corpus named CLES. |
K. Chen; G. Fu; Q. Chen; B. Hu; | icassp | 2021-05-16 |
779 | EASE: Extractive-Abstractive Summarization with Explanations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve the best of both worlds, we propose EASE, an extractive-abstractive framework for evidence-based text generation and apply it to document summarization. |
HAORAN LI et. al. | arxiv-cs.CL | 2021-05-14 |
780 | The Summary Loop: Learning to Write Abstractive Summaries Without Examples IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work presents a new approach to unsupervised abstractive summarization based on maximizing a combination of coverage and fluency for a given length constraint. |
Philippe Laban; Andrew Hsi; John Canny; Marti A. Hearst; | arxiv-cs.CL | 2021-05-11 |
781 | Long-Span Summarization Via Local Attention and Content Selection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we exploit large pre-trained transformer-based models and address long-span dependencies in abstractive summarization using two methods: local self-attention; and explicit content selection. |
Potsawee Manakul; Mark J. F. Gales; | arxiv-cs.CL | 2021-05-08 |
782 | Text Similarity Analysis for Evaluation of Descriptive Answers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Keeping in mind the necessity of intelligent system in educational sector, this paper proposes a text analysis based automated approach for automatic evaluation of the descriptive answers in an examination. |
Vedant Bahel; Achamma Thomas; | arxiv-cs.LG | 2021-05-06 |
783 | Genetic Algorithms For Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the strengths of Genetic Algorithms (GAs) for extractive summarization, as we hypothesized that GAs could construct more efficient solutions for the summarization task due to their relative customizability relative to deep learning models. |
William Chen; Kensal Ramos; Kalyan Naidu Mullaguri; Annie S. Wu; | arxiv-cs.CL | 2021-05-05 |
784 | Semantic Extractor-Paraphraser Based Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this manuscript, we propose an extractor-paraphraser based abstractive summarization system that exploits semantic overlap as opposed to its predecessors that focus more on syntactic information overlap. |
Anubhav Jangra; Raghav Jain; Vaibhav Mavi; Sriparna Saha; Pushpak Bhattacharyya; | arxiv-cs.CL | 2021-05-04 |
785 | The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In response to the above problems, the current research direction is predominantly divided into two categories, one is to design fact-aware evaluation metrics to select outputs without factual inconsistency errors, and the other is to develop new summarization systems towards factual consistency. In this survey, we focus on presenting a comprehensive review of these fact-specific evaluation methods and text summarization models. |
Yichong Huang; Xiachong Feng; Xiaocheng Feng; Bing Qin; | arxiv-cs.CL | 2021-04-30 |
786 | Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address these limitations, we devise a typology of factual errors and use it to collect human annotations of generated summaries from state-of-the-art summarization systems for the CNN/DM and XSum datasets. |
Artidoro Pagnoni; Vidhisha Balachandran; Yulia Tsvetkov; | arxiv-cs.CL | 2021-04-27 |
787 | Text Summarization of Czech News Articles Using Named Entities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose two abstractive summarization approaches based on Seq2Seq architecture. |
PETR MAREK et. al. | arxiv-cs.CL | 2021-04-21 |
788 | Attention-based Clinical Note Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we are applying a multi-head attention-based mechanism to perform extractive summarization of meaningful phrases on clinical notes. |
Neel Kanwal; Giuseppe Rizzo; | arxiv-cs.CL | 2021-04-18 |
789 | MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we improve multilingual text-to-text transfer Transformer with translation pairs (mT6). |
ZEWEN CHI et. al. | arxiv-cs.CL | 2021-04-17 |
790 | GupShup: An Annotated Corpus for Abstractive Summarization of Open-Domain Code-Switched Conversations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Towards this objective, we introduce abstractive summarization of Hindi-English code-switched conversations and develop the first code-switched conversation summarization dataset – GupShup, which contains over 6,831 conversations in Hindi-English and their corresponding human-annotated summaries in English and Hindi-English. |
LAIBA MEHNAZ et. al. | arxiv-cs.CL | 2021-04-17 |
791 | Multi-Perspective Abstractive Answer Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work introduces a novel dataset creation method to automatically create multi-perspective, bullet-point abstractive summaries from an existing CQA forum. |
Alexander R. Fabbri; Xiaojian Wu; Srini Iyer; Mona Diab; | arxiv-cs.CL | 2021-04-17 |
792 | $Q^{2}$: Evaluating Factual Consistency in Knowledge-Grounded Dialogues Via Question Generation and Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Inspired by recent work on evaluating factual consistency in abstractive summarization, we propose an automatic evaluation metric for factual consistency in knowledge-grounded dialogue using automatic question generation and question answering. |
OR HONOVICH et. al. | arxiv-cs.CL | 2021-04-16 |
793 | Unsupervised Extractive Summarization By Human Memory Simulation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle the problem of content selection in unsupervised extractive summarization of long, structured documents. |
Ronald Cardenas; Matthias Galle; Shay B. Cohen; | arxiv-cs.CL | 2021-04-16 |
794 | Planning with Learned Entity Prompts for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a simple but flexible mechanism to learn an intermediate plan to ground the generation of abstractive summaries. |
SHASHI NARAYAN et. al. | arxiv-cs.CL | 2021-04-15 |
795 | SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this limitation, we introduce SummVis, an open-source tool for visualizing abstractive summaries that enables fine-grained analysis of the models, data, and evaluation metrics associated with text summarization. |
Jesse Vig; Wojciech Kryściński; Karan Goel; Nazneen Fatema Rajani; | arxiv-cs.CL | 2021-04-15 |
796 | SummScreen: A Dataset for Abstractive Screenplay Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce SummScreen, a summarization dataset comprised of pairs of TV series transcripts and human written recaps. |
Mingda Chen; Zewei Chu; Sam Wiseman; Kevin Gimpel; | arxiv-cs.CL | 2021-04-14 |
797 | Constructing Contrastive Samples Via Summarization for Text Classification with Limited Annotations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel approach to construct contrastive samples for language tasks using text summarization. |
YANGKAI DU et. al. | arxiv-cs.CL | 2021-04-11 |
798 | Enhancing Scientific Papers Summarization with Citation Graph IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we redefine the task of scientific papers summarization by utilizing their citation graph and propose a citation graph-based summarization model CGSum which can incorporate the information of both the source paper and its references. |
CHENXIN AN et. al. | arxiv-cs.CL | 2021-04-07 |
799 | Spotify at TREC 2020: Genre-Aware Abstractive Podcast Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Since podcasts vary with respect to their genre, topic, and granularity of information, we propose two summarization models that explicitly take genre and named entities into consideration in order to generate summaries appropriate to the style of the podcasts. |
Rezvaneh Rezapour; Sravana Reddy; Ann Clifton; Rosie Jones; | arxiv-cs.CL | 2021-04-07 |
800 | Convex Aggregation for Opinion Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we revisit the commonly used simple average approach by examining the latent space and generated summaries. |
Hayate Iso; Xiaolan Wang; Yoshihiko Suhara; Stefanos Angelidis; Wang-Chiew Tan; | arxiv-cs.CL | 2021-04-03 |
801 | TL;DR: Out-of-Context Adversarial Text Summarization and Hashtag Recommendation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents Out-of-Context Summarizer, a tool that takes arbitrary public news articles out of context by summarizing them to coherently fit either a liberal- or conservative-leaning agenda. |
Peter Jachim; Filipo Sharevski; Emma Pieroni; | arxiv-cs.CL | 2021-04-01 |
802 | Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel embedding method for a text sequence (a phrase or a sentence) where each sequence is represented by a distinct set of multi-mode codebook embeddings to capture different semantic facets of its meaning. |
Haw-Shiuan Chang; Amol Agrawal; Andrew McCallum; | arxiv-cs.CL | 2021-03-29 |
803 | Extractive Summarization of Related Bug-fixing Comments in Support of Bug Repair Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Specifically, we combine Sentiment Analysis and the TextRank Model with the baseline Vector Space Model (VSM). |
Rrezarta Krasniqi; | arxiv-cs.SE | 2021-03-28 |
804 | Extractive Summarization of Call Transcripts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents an indigenously developed method that combines topic modeling and sentence selection with punctuation restoration in condensing ill-punctuated or un-punctuated call transcripts to produce summaries that are more readable. |
Pratik K. Biswas; Aleksandr Iakubovich; | arxiv-cs.CL | 2021-03-18 |
805 | Few-Shot Learning of An Interleaved Text Summarization Model By Pretraining with Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address this, we propose to pretrain an end-to-end trainable hierarchical encoder-decoder system using synthetic interleaved texts. |
Sanjeev Kumar Karn; Francine Chen; Yan-Ying Chen; Ulli Waltinger; Hinrich Schuetze; | arxiv-cs.CL | 2021-03-08 |
806 | IOT: Instance-wise Layer Reordering for Transformer Structures Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Based on this observation, in this work, we break the assumption of the fixed layer order in the Transformer and introduce instance-wise layer reordering into the model structure. |
JINHUA ZHU et. al. | arxiv-cs.CL | 2021-03-04 |
807 | Long Document Summarization in A Low Resource Setting Using Pretrained Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study a challenging low-resource setting of summarizing long legal briefs with an average source document length of 4268 words and only 120 available (document, summary) pairs. |
AHSAAS BAJAJ et. al. | arxiv-cs.CL | 2021-02-28 |
808 | Multichannel LSTM-CNN for Telugu Technical Domain Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we proposed the Multichannel LSTM-CNN methodology for Technical Domain Identification for Telugu. |
Sunil Gundapu; Radhika Mamidi; | arxiv-cs.CL | 2021-02-24 |
809 | Meta-Transfer Learning for Low-Resource Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to utilize two knowledge-rich sources to tackle this problem, which are large pre-trained models and diverse existing corpora. |
Yi-Syuan Chen; Hong-Han Shuai; | arxiv-cs.CL | 2021-02-18 |
810 | Centroid Transformers: Learning to Abstract with Attention IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose centroid attention, a generalization of self-attention that maps N inputs to M outputs $(M\leq N)$, such that the key information in the inputs are summarized in the smaller number of outputs (called centroids). |
Lemeng Wu; Xingchao Liu; Qiang Liu; | arxiv-cs.LG | 2021-02-17 |
811 | Entity-level Factual Consistency of Abstractive Text Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a set of new metrics to quantify the entity-level factual consistency of generated summaries and we show that the entity hallucination problem can be alleviated by simply filtering the training data. |
FENG NAN et. al. | arxiv-cs.CL | 2021-02-17 |
812 | Non-Autoregressive Text Generation with Pre-trained Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we show that BERT can be employed as the backbone of a NAG model to greatly improve performance. |
YIXUAN SU et. al. | arxiv-cs.CL | 2021-02-16 |
813 | Unsupervised Extractive Summarization Using Pointwise Mutual Information IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose new metrics of relevance and redundancy using pointwise mutual information (PMI) between sentences, which can be easily computed by a pre-trained language model. |
Vishakh Padmakumar; He He; | arxiv-cs.CL | 2021-02-11 |
814 | Fact-Enhanced Synthetic News Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To better understand the potential threats of synthetic news, we develop a novel generation method FACTGEN to generate high-quality news content. |
Kai Shu; Yichuan Li; Kaize Ding; Huan Liu; | aaai | 2021-02-09 |
815 | Exploring Explainable Selection to Control Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Therefore, to begin prying open the black box and to inject a level of control into the substance of the final summary, we developed a novel select-and-generate framework that focuses on explainability. |
Haonan Wang; Yang Gao; Yu Bai; Mirella Lapata; Heyan Huang; | aaai | 2021-02-09 |
816 | Adaptive Prior-Dependent Correction Enhanced Reinforcement Learning for Natural Language Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the issue, we propose a technique called adaptive prior-dependent correction (APDC) to enhance RL. |
Wei Cheng; Ziyan Luo; Qiyue Yin; | aaai | 2021-02-09 |
817 | Unsupervised Abstractive Dialogue Summarization for Tete-a-Tetes IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose the first unsupervised abstractive dialogue summarization model for tete-a-tetes (SuTaT). |
Xinyuan Zhang; Ruiyi Zhang; Manzil Zaheer; Amr Ahmed; | aaai | 2021-02-09 |
818 | We Can Explain Your Research in Layman’s Terms: Towards Automating Science Journalism at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose to study Automating Science Journalism (ASJ), the process of producing a layman’s terms summary of a research article, as a new benchmark for long neural abstractive summarization and story generation. |
RUMEN DANGOVSKI et. al. | aaai | 2021-02-09 |
819 | Flexible Non-Autoregressive Extractive Summarization with Threshold: How to Extract A Non-Fixed Number of Summary Sentences IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a more flexible and accurate non-autoregressive method for single document extractive summarization, extracting a non-fixed number of summary sentences without the sorting step. |
RUIPENG JIA et. al. | aaai | 2021-02-09 |
820 | Unsupervised Opinion Summarization with Content Planning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We show that explicitly incorporating content planning in a summarization model not only yields output of higher quality, but also allows the creation of synthetic datasets which are more natural, resembling real world document-summary pairs. |
Reinald Kim Amplayo; Stefanos Angelidis; Mirella Lapata; | aaai | 2021-02-09 |
821 | Contextualized Rewriting for Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate contextualized rewriting, which ingests the entire original document. |
Guangsheng Bao; Yue Zhang; | arxiv-cs.CL | 2021-01-31 |
822 | Fairness for Whom? Understanding The Reader’s Perception of Fairness in Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a human-in-the-loop metric and an automated graph-based methodology to quantify the perceived bias in textual summaries. |
Anurag Shandilya; Abhisek Dash; Abhijnan Chakraborty; Kripabandhu Ghosh; Saptarshi Ghosh; | arxiv-cs.IR | 2021-01-29 |
823 | How to Evaluate A Summarizer: Study Design and Statistical Analysis for Manual Linguistic Quality Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We conduct two evaluation experiments on two aspects of summaries’ linguistic quality (coherence and repetitiveness) to compare Likert-type and ranking annotations and show that best choice of evaluation method can vary from one aspect to another. |
Julius Steen; Katja Markert; | arxiv-cs.CL | 2021-01-27 |
824 | Unsupervised Abstractive Summarization of Bengali Text Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To overcome this problem, we propose a graph-based unsupervised abstractive summarization system in the single-document setting for Bengali text documents, which requires only a Part-Of-Speech (POS) tagger and a pre-trained language model trained on Bengali texts. We also provide a human-annotated dataset with document-summary pairs to evaluate our abstractive model and to support the comparison of future abstractive summarization systems of the Bengali Language. |
Radia Rayan Chowdhury; Mir Tafseer Nayeem; Tahsin Tasnim Mim; Md. Saifur Rahman Chowdhury; Taufiqul Jannat; | arxiv-cs.CL | 2021-01-26 |
825 | Neural Abstractive Text Summarizer for Telugu Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we are proposing an abstractive text summarization Deep learning model for Telugu language. |
Mohan Bharath B; Aravindh Gowtham B; Akhil M; | arxiv-cs.CL | 2021-01-18 |
826 | Summaformers @ LaySumm 20, LongSumm 20 IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we specifically look at the problem of summarizing scientific research papers from multiple domains. |
Sayar Ghosh Roy; Nikhil Pinnaparaju; Risubh Jain; Manish Gupta; Vasudeva Varma; | arxiv-cs.CL | 2021-01-10 |
827 | Generating Informative CVE Description From ExploitDB Posts By Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To assist in documenting CVEs for the ExploitDB posts, we propose an open information method to extract 9 key vulnerability aspects (vulnerable product/version/component, vulnerability type, vendor, attacker type, root cause, attack vector and impact) from the verbose and noisy ExploitDB posts. |
JIAMOU SUN et. al. | arxiv-cs.LG | 2021-01-05 |
828 | News Image Steganography: A Novel Architecture Facilitates The Fake News Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes an architecture named News Image Steganography (NIS) to reveal the aforementioned inconsistency through image steganography based on GAN. |
Jizhe Zhou; Chi-Man Pun; Yu Tong; | arxiv-cs.CV | 2021-01-03 |
829 | Text Summarization of News Events Using Semantic Triples Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shikha Singh; Garima Srivastava; | International Journal of Computer Trends and Technology | 2021-01-01 |
830 | Text Coherence Analysis Based on Misspelling Oblivious Word Embeddings and Deep Neural Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text coherence analysis is the most challenging task in Natural Language Processing (NLP) than other subfields of NLP, such as text generation, translation, or text summarization. … |
Md. Anwar Hussen Wadud; Md. Rashadul; | International Journal of Advanced Computer Science and … | 2021-01-01 |
831 | Paht_nlp @ MEDIQA 2021: Multi-grained Query Focused Multi-Answer Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this article, we describe our systems for the MEDIQA 2021 Shared Tasks. First, we will describe our method for the second task, Multi-Answer Summarization (MAS). For extractive … |
WEI ZHU et. al. | 2021-01-01 | |
832 | Text Summarization Using Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View |
G. Sreenivasulu; N. Thulasi Chitra; B. Sujatha; K. Venu Madhav; | Information and Communication Technology for Competitive … | 2021-01-01 |
833 | Improving Abstractive Dialogue Summarization with Hierarchical Pretraining and Topic Segment IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the increasing abundance of meeting transcripts, meeting summary has attracted more and more attention from researchers. The unsupervised pre-training method based on … |
MengNan Qi; Hao Liu; Yuzhuo Fu; Ting Liu; | Conference on Empirical Methods in Natural Language … | 2021-01-01 |
834 | Two-Stage Encoder for Pointer-Generator Network with Pretrained Embeddings Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization has become the mainstream of automatic text summarization because of its unique flexibility. Pointer-Generator Network(PGN) has already been the de facto … |
Zhou Lin; Qifeng Zhou; Langcai Cao; | 2021 16th International Conference on Computer Science & … | 2021-01-01 |
835 | Extractive Summarization of Text Using Weighted Average of Feature Scores Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shatajbegum Nadaf; Vidyagouri B. Hemadri; | 2021-01-01 | |
836 | TransVae:A Novel Variational Sequence-to-Sequence Framework for Semi-supervised Learning and Diversity Improvement Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text generation tasks require that the generated text have certain diversity while ensuring the relevance. Traditional Seq2Seq models usually use cross entropy as the objective … |
XINYI WANG et. al. | 2021 International Joint Conference on Neural Networks … | 2021-01-01 |
837 | Resilient Abstractive Summarization Model with Adaptively Weighted Training Loss Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, abstractive summarization models are preferred over extractive summarization models as they can generate words that do not exist in the original text, whose summary … |
Shiqi Guo; Jing Zhao; Shiliang Sun; | 2021 International Joint Conference on Neural Networks … | 2021-01-01 |
838 | Extractive Multi Document Summarization Using Harmony Search Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The exponential growth of information on the internet makes it troublesome for users to get valuable information. Text summarization is the process to overcome such a problem. An … |
Zuhair Hussein Ali; Ahmed Kawther Hussein; Haithem Kareem Abass; Elham Fadel; | TELKOMNIKA Telecommunication Computing Electronics and … | 2021-01-01 |
839 | Personalized Extractive Summarization for A News Dialogue System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In modern society, people’s interests and preferences are diversifying. Along with this, the demand for personalized summarization technology is increasing. In this study, we … |
HIROAKI TAKATSU et. al. | 2021 IEEE Spoken Language Technology Workshop (SLT) | 2021-01-01 |
840 | An Empirical Study of Deep Learning Models for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Neha Rane; Sharvari Govilkar; | 2021-01-01 | |
841 | Abstractive Text Summarization Approaches with Analysis of Evaluation Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View |
Abdullah Faiz Ur Rahman Khilji; Utkarsh Sinha; Pintu Singh; Adnan Ali; Partha Pakray; | 2021-01-01 | |
842 | EWNStream+: Effective and Real-time Clustering of Short Text Streams Using Evolutionary Word Relation Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The real-time clustering of short text streams has various applications, such as event tracking, text summarization and sentimental analysis. However, accurately and efficiently … |
Shuiqiao Yang; Guangyan Huang; Xiangmin Zhou; Vicky H. Mak-Hau; John Yearwood; | Int. J. Inf. Technol. Decis. Mak. | 2021-01-01 |
843 | A Hybrid Deep Learning Architecture for Opinion-oriented Multi-document Summarization Based on Multi-feature Fusion IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Opinion summarization is a process to produce concise summaries from a large number of opinionated texts. In this paper, we present a novel deep-learning-based method for the … |
Asad Abdi; Shafaatunnur Hasan; Siti Mariyam Hj. Shamsuddin; Norisma Idris; Jalil Piran; | Knowl. Based Syst. | 2021-01-01 |
844 | Effective Deep Neural Network Method Based Sentimental Analysis for Social Media Health Care Information Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the advent of natural language processing and machine learning techniques, Sentimental Analysis (SA) is receiving attention among various communities due to interpreting and … |
D. Sasikala; | 2021-01-01 | |
845 | Parts of Speech Tagging and Extractive Summarization Techniques for Kannada Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summaries of documents were initially done manually, but today, huge data is available on the Internet and everywhere, where manual summarization is failing miserably. A massive … |
Alaka Ananth; Sachin Bhat; Rushali Naik; U. Pooja Nair; | 2021-01-01 | |
846 | History Reuse and Bag-of-Words Loss for Long Summary Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recurrent Neural Network (RNN) based abstractive text summarization models have made great progress over the past few years, largely triggered by the encoder-decoder architecture. … |
Qing Liu; Lei Chen; Yuan Yuan; Huarui Wu; | IEEE/ACM Transactions on Audio, Speech, and Language … | 2021-01-01 |
847 | A Grammar-Aware Pointer Network for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yinghua Zhou; Fang Cao; Yangyang Cao; Ning Yang; Zhen Li; | 2021-01-01 | |
848 | Evaluation of Text-Summarization Technique Related Papers Related Patents Related Grants Related Venues Related Experts View |
Manju Khari; Renu Dalal; Arush Sharma; Avinash Dubey; | Multimodal Biometric Systems | 2021-01-01 |
849 | Cross-lingual Fine-tuning for Abstractive Arabic Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While abstractive summarization in certain languages, like English, has already reached fairly good results due to the availability of trend-setting resources, like the CNN/Daily … |
Mram Kahla; Zijian Győző Yang; Attila Novák; | 2021-01-01 | |
850 | Abstractive Multi Document Text Summarization of User Reviews Using Graph Generation and TF-IDF Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the increase in number of e-commerce sites, one finds it difficult to choose and buy a product. It is not possible for a person to read hundreds of product reviews from … |
Soma Shrenika; | 2021-01-01 | |
851 | Let’s Summarize Scientific Documents! A Clustering-Based Approach Via Citation Context Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Scientific documents are getting published at expanding rates and create challenges for the researchers to keep themselves up to date with the new developments. Scientific … |
Santosh Kumar Mishra; Naveen Saini; Sriparna Saha; Pushpak Bhattacharyya; | 2021-01-01 | |
852 | Comparative Analysis of Models for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Minakshi Tomer; Manoj Kumar; | Advances in Intelligent Systems and Computing | 2021-01-01 |
853 | A Framework for Generating Extractive Summary from Multiple Malayalam Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic extractive text summarization retrieves a subset of data that represents most notable sentences in the entire document. In the era of digital explosion, which is mostly … |
K. Manju; S. David Peter; Sumam Mary Idicula; | Inf. | 2021-01-01 |
854 | Gated Graph Neural Attention Networks for Abstractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Sequence to sequence (Seq2Seq) model for abstractive summarization have aroused widely attention due to their powerful ability to represent sequence. However, the sequence … |
Zeyu Liang; Junping Du; Yingxia Shao; Houye Ji; | Neurocomputing | 2021-01-01 |
855 | Global Agendas: Detection of Agenda Shifts in Cross-National Discussions Using Neural-Network Text Summarization for Twitter Related Papers Related Patents Related Grants Related Venues Related Experts View |
Svetlana S. Bodrunova; Ivan S. Blekanov; Nikita Tarasov; | 2021-01-01 | |
856 | T-BERTSum: Topic-Aware Text Summarization Based on BERT IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
TINGHUAI MA et. al. | IEEE Transactions on Computational Social Systems | 2021-01-01 |
857 | An Approach for Multi-Document Text Summarization Using Extreme Learning Machine and LexRank Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wedad Abdul Khuder Naser; | International Journal of Engineering Research and Advanced … | 2021-01-01 |
858 | Joint Knowledge-powered Topic Level Attention for A Convolutional Text Summarization Model Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shirin Akther Khanam; Fei Liu; Yi-Ping Phoebe Chen; | Knowl. Based Syst. | 2021-01-01 |
859 | Multilingual Text Summarization Using Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rana Talib AlTimimi; Fatma Hassan AlRubbiay; | International Journal of Engineering Research and Advanced … | 2021-01-01 |
860 | ISSumSet: A Tweet Summarization Dataset Hidden in A TREC Track IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A key issue for Twitter users relates to the summarization of the continuous and overwhelming stream of information. Many approaches for tweet summarization were proposed in the … |
Alexis Dusart; Karen Pinel-Sauvagnat; Gilles Hubert; | Proceedings of the 36th Annual ACM Symposium on Applied … | 2021-01-01 |
861 | Application of Graph Neural Network in Automatic Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rui Luo; Shan Zhao; Zhiping Cai; | 2021-01-01 | |
862 | Text Summarization System: An Extractive Approach Using Hierarchical Text Clustering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The need for summarizing texts evolves from the large amount of data present in electronic channels which leads to distraction of users and wastage of their time. There are … |
Francisca O. Oladipo; Abdulaziz Baba-Ali Ohiani; | International Journal of Computer Applications | 2021-01-01 |
863 | Recent Approaches for Text Summarization Using Machine Learning & LSTM0 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Neeraj Kumar Sirohi; Mamta Bansal; S. N. Rajan; | Journal of Big Data | 2021-01-01 |
864 | Using Question Answering Rewards to Improve Abstractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Neural abstractive summarization models have drastically improved in the recent years. However, the summaries generated by these models generally suffer from issues such as: not … |
Chulaka Gunasekara; G. Feigenblat; Benjamin Sznajder; R. Aharonov; Sachindra Joshi; | Conference on Empirical Methods in Natural Language … | 2021-01-01 |
865 | A Feature-Augmented Deep Learning Model for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Bui Thi Mai Anh; Nguyen Thi Thu Trang; | 2021-01-01 | |
866 | Unsupervised Extractive Multi-document Summarization Method Based on Transfer Learning from BERT Multi-task Fine-tuning IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text representation is a fundamental cornerstone that impacts the effectiveness of several text summarization methods. Transfer learning using pre-trained word embedding models … |
Salima Lamsiyah; Abdelkader El Mahdaouy; Said El Alaoui Ouatik; Bernard Espinasse; | Journal of Information Science | 2021-01-01 |
867 | D-MmT: A Concise Decoder-only Multi-modal Transformer for Abstractive Summarization in Videos Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multi-modal abstractive summarization for videos is an emerging task, aiming to integrate multi-modal and multi-source inputs (video, audio transcript) into a compressed textual … |
Nayu Liu; Xian Sun; Hongfeng Yu; Wenkai Zhang; Guangluan Xu; | Neurocomputing | 2021-01-01 |
868 | Extractive Summarization Using Frequency Driven Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
V. MOHAN KALYAN et. al. | 2021-01-01 | |
869 | A Review of Graph-Based Extractive Text Summarization Models Related Papers Related Patents Related Grants Related Venues Related Experts View |
Abdulkadir Abubakar Bichi; Ruhaidah Samsudin; Rohayanti Hassan; Khalil Almekhlafi; | 2021-01-01 | |
870 | Text Summarization and Classification for Indian Language Related Papers Related Patents Related Grants Related Venues Related Experts View |
Manasi Chouk; Neelam Phadnis; | International Journal of Computer Applications | 2021-01-01 |
871 | A Generative Text Summarization Model Based on Document Structure Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Haihui Huang; Maohong Zha; | 2021-01-01 | |
872 | Study of Automatic Text Summarization Approaches in Different Languages IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays we see huge amount of information is available on both, online and offline sources. For single topic we see hundreds of articles are available, containing vast amount of … |
Yogesh Kumar; Komalpreet Kaur; Sukhpreet Kaur; | Artif. Intell. Rev. | 2021-01-01 |
873 | Automatic Extractive Summarization for English Text: A Brief Survey Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, due to the popularity of the Internet, digital documents are growing at an exponential rate on the Web. To save time and quickly know about the document(s), a … |
Sunil Dhankhar; Mukesh Kumar Gupta; | Proceedings of Second Doctoral Symposium on Computational … | 2021-01-01 |
874 | An Efficient Single Document Arabic Text Summarization Using A Combination of Statistical and Semantic Features IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The exponential growth of online textual data triggered the crucial need for an effective and powerful tool that automatically provides the desired content in a summarized form … |
Aziz Qaroush; Ibrahim Abu Farha; Wasel Ghanem; Mahdi Washaha; Eman Maali; | J. King Saud Univ. Comput. Inf. Sci. | 2021-01-01 |
875 | Goal-Directed Extractive Summarization of Financial Reports Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Financial reports filed by various companies discuss compliance, risks, and future plans, such as goals and new projects, which directly impact their stock price. Quick … |
Yash Agrawal; Vivek Anand; Manish Gupta; S. Arunachalam; Vasudeva Varma; | Proceedings of the 30th ACM International Conference on … | 2021-01-01 |
876 | Contour: Penalty and Spotlight Mask for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Trang-Phuong N. Nguyen; Nhi-Thao Tran; | 2021-01-01 | |
877 | Extractive Multi-document Text Summarization Using Dolphin Swarm Optimization Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, extracting the desired information from internet source is a challenging task because of a large amount of information available on the internet. So, we propose a new … |
Atul Kumar Srivastava; Dhiraj Pandey; Alok Agarwal; | Multimedia Tools and Applications | 2021-01-01 |
878 | IceSum: An Icelandic Text Summarization Corpus Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic Text Summarization (ATS) is the task of generating concise and fluent summaries from one or more documents. In this paper, we present IceSum, the first Icelandic corpus … |
Jón Dadason; Hrafn Loftsson; Salome Sigurdardóttir; Torsteinn Björnsson; | 2021-01-01 | |
879 | A Comparative Review of Extractive Text Summarization in Indonesian Language Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization has important role in natural language processing. One of text summarization type is extractive summarization. Research on text summarization in Indonesian … |
W Widodo; M Nugraheni; I P Sari; | IOP Conference Series: Materials Science and Engineering | 2021-01-01 |
880 | Automated Multi-document Text Summarization from Heterogeneous Data Sources Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mahsa Abazari Kia; | 2021-01-01 | |
881 | An Effective Deep Learning Approach for Extractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Minh-Tuan Luu; Thanh-Huong Le; Minh-Tan Hoang; | 2021-01-01 | |
882 | 4W1H Keyword Extraction Based Summarization Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this internet era, with rapidly growing online information, there is a need for automatic summarization of textual documents from plethora of available information, making it … |
Seungyeon Lee; Taewon Park; Minho Lee; | 2021 International Conference on Electronics, Information, … | 2021-01-01 |
883 | HG-News: News Headline Generation Based on A Generative Pre-Training Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural headline generation models have recently shown great results since neural network methods have been applied to text summarization. In this paper, we focus on news headline … |
Ping Li; Jiong Yu; Jiaying Chen; Binglei Guo; | IEEE Access | 2021-01-01 |
884 | Improving Semantic Coherence of Gujarati Text Topic Model Using Inflectional Forms Reduction and Single-letter Words Removal Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A topic model is one of the best stochastic models for summarizing an extensive collection of text. It has accomplished an inordinate achievement in text analysis as well as text … |
Uttam Chauhan; Apurva Shah; | ACM Transactions on Asian and Low-Resource Language … | 2021-01-01 |
885 | An Unsupervised Method for Extractive Multi-document Summarization Based on Centroid Approach and Sentence Embeddings IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive multi-document summarization (MDS) is the process of automatically summarizing a collection of documents by ranking sentences according to their importance and … |
Salima Lamsiyah; Abdelkader El Mahdaouy; Bernard Espinasse; Said El Alaoui Ouatik; | Expert Syst. Appl. | 2021-01-01 |
886 | A Weighted Word Embedding Based Approach for Extractive Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization (ATS) is a method to condense a long size text document into abridging form by enveloping all the primary information and central theme. Numerous ATS … |
Ruby Rani; Daya K. Lobiyal; | Expert Syst. Appl. | 2021-01-01 |
887 | An Improved Key Term Weightage Algorithm for Text Summarization Using Local Context Information and Fuzzy Graph Sentence Score Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The process of text summarization is to identify the crux of the document. In the proposed work, summarization is done using three different algorithms. They are sentence based … |
T. Vetriselvi; N. P. Gopalan; | Journal of Ambient Intelligence and Humanized Computing | 2021-01-01 |
888 | A Deep Look Into Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This investigation has presented an approach to Extractive Automatic Text Summarization (EATS). A framework focused on the summary of a single document has been developed, using … |
Jhonathan Quillo-Espino; Rosa María Romero-González; Ana-Marcela Herrera-Navarro; | Journal of Computational Chemistry | 2021-01-01 |
889 | Strong Natural Language Query Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we propose a novel query generation task we refer to as the Strong Natural Language Query (SNLQ) problem. The key idea we explore is how to best learn document … |
Binsheng Liu; Xiaolu Lu; J. Shane Culpepper; | Inf. Retr. J. | 2021-01-01 |
890 | Extractive Text Summarization of Student Essay Assignment Using Sentence Weight Features and Fuzzy C-Means Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: One of the main tasks of a lecturer is to give students an academic assessment in the learning process. The assessment process begins with reading or checking the answers of … |
I Made Suwija Putra; Yonatan Adiwinata; Desy Purnami Singgih Putri; Ni Putu Sutramiani; | International journal of artificial intelligence | 2021-01-01 |
891 | Keyword-Aware Encoder for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tianxiang Hu; Jingxi Liang; Wei Ye; Shikun Zhang; | 2021-01-01 | |
892 | Unsupervised Neural Networks for Automatic Arabic Text Summarization Using Document Clustering and Topic Modeling IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nabil Alami; Mohammed Meknassi; Noureddine Ennahnahi; Yassine El Adlouni; Ouafae Ammor; | Expert Syst. Appl. | 2021-01-01 |
893 | Text Summarization As The Potential Technology for Intelligent Internet of Things Related Papers Related Patents Related Grants Related Venues Related Experts View |
Lijun Wei; Yun Liu; Jian Li; | 2021-01-01 | |
894 | Project Reporting Management System with AI Based Assistive Features for Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper details a proof-of-concept system called Project Reporting Management System (PRMS) to manage the project reporting process in a typical research centre where the … |
Jin Boon Benjamin Tan; Quan Chen; Chai Kiat Yeo; | International Journal of Machine Learning and Computing | 2021-01-01 |
895 | A Quantum-Inspired Genetic Algorithm for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization has recently become a key instrument for reducing the huge quantity of textual data. In this paper, the authors propose a quantum-inspired genetic … |
Khadidja Chettah; Amer Draa; | Int. J. Nat. Comput. Res. | 2021-01-01 |
896 | A Novel Extractive Multi-document Text Summarization System Using Quantum-inspired Genetic Algorithm: MTSQIGA IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mohammad Mojrian; Seyed Abolghasem Mirroshandel; | Expert Syst. Appl. | 2021-01-01 |
897 | Keyphrase Extraction from Scientific Articles Via Extractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Automatically extracting keyphrases from scholarly documents leads to a valuable concise representation that humans can understand and machines can process for tasks, such as … |
Chrysovalantis Giorgos Kontoulis; Eirini Papagiannopoulou; Grigorios Tsoumakas; | 2021-01-01 | |
898 | The Effect of Pretraining on Extractive Summarization for Scientific Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large pretrained models have seen enormous success in extractive summarization tasks. In this work, we investigate the influence of pretraining on a BERT-based extractive … |
YASH GUPTA et. al. | 2021-01-01 | |
899 | ForumSum: A Multi-Speaker Conversation Summarization Dataset IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization quality had large improvements since recent language pretraining techniques. However, currently there is a lack of datasets for the growing needs of … |
Misha Khalman; Yao Zhao; Mohammad Saleh; | Conference on Empirical Methods in Natural Language … | 2021-01-01 |
900 | Text Summarization and Dimensionality Reduction Using Ranking and Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
Dipti Bartakke; Santosh Kumar; Aparna Junnarkar; Somnath B. Thigale; | 2021-01-01 | |
901 | Enhancements of Attention-Based Bidirectional LSTM for Hybrid Automatic Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The automatic generation of a text summary is a task of generating a short summary for a relatively long text document by capturing its key information. In the past, supervised … |
JIAWEN JIANG et. al. | IEEE Access | 2021-01-01 |
902 | Summarization of Legal Documents: Where Are We Now and The Way Forward IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to huge amount of legal information availability on the internet, as well as other sources, it is important for the research community to do more extensive research on the … |
Deepali Jain; Malaya Dutta Borah; Anupam Biswas; | Comput. Sci. Rev. | 2021-01-01 |
903 | Enhancing Language Generation with Effective Checkpoints of Pre-trained Language Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This work empirically explores effective exploiting of intermediate output from pretrained language models (PrLMs) for language generation tasks. For this purpose, we propose an … |
Jeonghyeok Park; Hai Zhao; | 2021-01-01 | |
904 | Biomedical Text Summarization Based on The Itemset Mining Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The expanding amount of text-based biomedical information has prompted mining valuable or intriguing frequent patterns (words/terms) from extremely massive content, which is still … |
Supriya Gupta; Aakanksha Sharaff; Naresh Kumar Nagwani; | Advances in Data Mining and Database Management | 2021-01-01 |
905 | An Online Multi-source Summarization Algorithm for Text Readability in Topic-based Search IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Web search users are likely to face problems related to the availability of large amounts of data. As the quantity of online content grows, the risk of missing relevant … |
Arturo Curiel; Claudio Gutiérrez-Soto; José Rafael Rojano-Cáceres; | Comput. Speech Lang. | 2021-01-01 |
906 | Recommending The Title of A Research Paper Based on Its Abstract Using Deep Learning-Based Text Summarization Approaches Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sheetal Bhati; Shweta Taneja; Pinaki Chakraborty; | Advances in Intelligent Systems and Computing | 2021-01-01 |
907 | WILSON: A Divide and Conquer Approach for Fast and Effective News Timeline Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Major news media frequently uses the method of news timeline summarization to summarize important daily news over major events across the timeline. While various sophisticated … |
Yiming Liao; Shuguang Wang; Dongwon Lee; | 2021-01-01 | |
908 | Contrastive Aligned Joint Learning for Multilingual Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Multilingual text summarization requires the ability to understand documents in multiple languages and generate summaries in the corresponding language, which poses more … |
Danqing Wang; Jiaze Chen; Hao Zhou; Xipeng Qiu; Lei Li; | 2021-01-01 | |
909 | WATS-SMS: A T5-Based French Wikipedia Abstractive Text Summarizer for SMS Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization remains a challenging task in the natural language processing field despite the plethora of applications in enterprises and daily life. One of the common use … |
Jean Louis Fendji Kedieng Ebongue; Désiré Manuel Taira; Marcellin Atemkeng; Adam Musa Ali; | Future Internet | 2021-01-01 |
910 | An Interactive Query-based Approach for Summarizing Scientific Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Purpose Query-based summarization approaches might not be able to provide summaries compatible with the user’s information need, as they mostly rely on a limited source of … |
Farnoush Bayatmakou; Azadeh Mohebi; Abbas Ahmadi; | 2021-01-01 | |
911 | Headnote Prediction Using Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Headnotes are the precise explanation and summary of legal points in an issued judgment. Law journals hire experienced lawyers to write these headnotes. These headnotes help the … |
Sarmad Mahar; Sahar Zafar; Kamran Nishat; | Int. Arab J. Inf. Technol. | 2021-01-01 |
912 | Topic Centric Korean Text Summarization Using Attribute Model Related Papers Related Patents Related Grants Related Venues Related Experts View |
Su-Hwan Yoon; A-Yeong Kim; Seong-Bae Park; | Journal of KIISE | 2021-01-01 |
913 | Can Text Summarization Enhance The Headline Stance Detection Task? Benefits and Drawbacks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Marta Esther Vicente; Robiert Sepúlveda-Torres; Cristina Barros; Estela Saquete Boró; Elena Lloret; | 2021-01-01 | |
914 | DOFM: Domain Feature Miner for Robust Extractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The domain feature retrieval has potential applications in text summarization. However, it is challenging to mine domain features from the user reviews. In this paper, a novel … |
Hiren Kumar Thakkar; Prasan Kumar Sahoo; Pranab Mohanty; | Inf. Process. Manag. | 2021-01-01 |
915 | Automatic Summarizing The News from Inform.kz By Using Natural Language Processing Tools Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid rise of the information on the web brought up new problems of data access and processing. Therefore there is a need for tools that will help to overcome the problem of … |
Bakdaulet Kynabay; Aimoldir Aldabergen; Azamat Zhamanov; | 2021 IEEE International Conference on Smart Information … | 2021-01-01 |
916 | Extractive Text Summarization Based on Selectivity Ranking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive summarization of text documents deals with automatic creation of a summary by combining the most salient sentences extracted from the original text document into a more … |
Dino Aljevic; Ljupco Todorovski; Sanda Martincic-Ipsic; | 2021 International Conference on INnovations in Intelligent … | 2021-01-01 |
917 | GOW-Stream: A Novel Approach of Graph-of-words Based Mixture Model for Semantic-enhanced Text Stream Clustering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, rapid growth of social networks and online news resources from Internet have made text stream clustering become an insufficient application in multiple domains (e.g.: … |
Tham Vo; Phuc Do; | Intell. Data Anal. | 2021-01-01 |
918 | Globalizing BERT-based Transformer Architectures for Long Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Fine-tuning a large language model on downstream tasks has become a commonly adopted process in the Natural Language Processing (NLP) (CITATION). However, such a process, when … |
Quentin Grail; | 2021-01-01 | |
919 | ScatterPlotAnalyzer: Digitizing Images of Charts Using Tensor-Based Computational Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Charts or scientific plots are widely used visualizations for efficient knowledge dissemination from datasets. Nowadays, these charts are predominantly available in image format … |
Komal Dadhich; Siri Chandana Daggubati; Jaya Sreevalsan-Nair; | 2021-01-01 | |
920 | Evaluation of Text Summaries Without Human References Based on The Linear Optimization of Content Metrics Using A Genetic Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Evaluation of Text Summaries (ETS) has been a task of constant challenges to the development of Automatic Text Summarization (ATS). Within the ATS task, the ETS is crucial to … |
Jonathan Rojas Simón; Yulia Ledeneva; René Arnulfo García-Hernández; | Expert Syst. Appl. | 2021-01-01 |
921 | Detection of Multiword Expressions with Word Vector Representations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multiword expressions (MWE) are word combinations where multiple words leave their own meaning to build a new one. These word combinations are important in text summarization, … |
Tansu Tasçioglu; Senem Kumova Metin; | 2021 29th Signal Processing and Communications Applications … | 2021-01-01 |
922 | Reinforced Abstractive Text Summarization With Semantic Added Reward Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is an important task in natural language processing (NLP). Neural summary models summarize information by understanding and rewriting documents through the … |
Heewon Jang; Wooju Kim; | IEEE Access | 2021-01-01 |
923 | A Finer-grain Universal Dialogue Semantic Structures Based Model For Abstractive Dialogue Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although abstractive summarization models have achieved impressive results on document summarization tasks, their performance on dialogue modeling is much less satisfactory due to … |
Yuejie Lei; Fujia Zheng; Yuanmeng Yan; Keqing He; Weiran Xu; | Conference on Empirical Methods in Natural Language … | 2021-01-01 |
924 | ASM: Augmentation-based Semantic Mechanism on Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Many transformer-based encoder-decoder models have made significant progress on summary generating tasks. And the availability of pre-trained models further improves its … |
Weidong Ren; Hao Zhou; Gongshen Liu; Fei Huan; | 2021 International Joint Conference on Neural Networks … | 2021-01-01 |
925 | Automatic Video Summarization with Timestamps Using Natural Language Processing Text Fusion Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In videos, description and keywords play an important role in the choosing process of the right video to watch. The main idea of the proposed approach is to generate descriptions … |
AHMED EMAD et. al. | 2021 IEEE 11th Annual Computing and Communication Workshop … | 2021-01-01 |
926 | Development of Technology for Summarization of Kazakh Text Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper presents the solution to the problem of summarizing Kazakh texts. The problem of Kazakh text summarization is considered as a sequence of two tasks: extracting the most … |
Talgat Zhabayev; Ualsher Tukeyev; | International Journal of Advanced Computer Science and … | 2021-01-01 |
927 | An Empirical Analysis of Similarity Based Single Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In current days, there is an enormous amount of information available in various resources like www, e-books, tweets, several articles, and social media posts. Human beings have … |
Siba Prasad Pati; Rasmita Rautray; | 2021 5th International Conference on Computing … | 2021-01-01 |
928 | A Comparison of Methods for The Evaluation of Text Summarization Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic Text Summarization techniques aim to extract key information from one or more input texts automatically, producing summaries and preserving the meaning of content. These … |
Marcello Barbella; Michele Risi; Genny Tortora; | 2021-01-01 | |
929 | Element Graph-augmented Abstractive Summarization for Legal Public Opinion News with Graph Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic summarization for legal public opinion news has been an attractive research problem in recent years. Compared with the open-domain, summarization for legal public … |
Yuxin Huang; Zhengtao Yu; Junjun Guo; Yan Xiang; Yantuan Xian; | Neurocomputing | 2021-01-01 |
930 | Learning to Rank for Text Summarization: Revisiting The Features and Methods for Turkish Bank Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study revisits features and learning to rank algorithms for domain specific Turkish text summarization. In this study, we elaborate on the effect of sentence-level and … |
Furkan Göz; Fehmi Sener; Alev Mutlu; Kerem Küçük; Mahir Temur; | 2021 International Conference on INnovations in Intelligent … | 2021-01-01 |
931 | MTStemmer: A Multilevel Stemmer for Effective Word Pre-processing in Marathi Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Article History: Received: 10 November 2020; Revised: 12 January 2021; Accepted: 27 January 2021; Published online: 05 April 2021 Abstract: In natural language processing, it is … |
Et. al. Virat Giri; | 2021-01-01 | |
932 | CESumm: Semantic Graph-Based Approach for Extractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
S. Gokul Amuthan; S. Chitrakala; | Algorithms for Intelligent Systems | 2021-01-01 |
933 | Multi-document Arabic Text Summarization Based on Thematic Annotation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Reduce document(s) by keeping keys and significant sentences from a set of data is called text summarization. It has been around for a long time in natural language processing … |
Amina Merniz; Anja Habacha Chaïbi; Henda Hajjami Ben Ghézala; | 2021-01-01 | |
934 | Implementation of Automatic Text Summarization with TextRank Method in The Development of Al-Qur’an Vocabulary Encyclopedia IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Muhamad Fahmi Fakhrezi; M. Bijaksana; A. Huda; | Procedia Computer Science | 2021-01-01 |
935 | Text Summarization Using Topic-based Vector Space Model and Semantic Measure IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ramesh Chandra Belwal; Sawan Rai; Atul Gupta; | Inf. Process. Manag. | 2021-01-01 |
936 | Automatic Text Summarization for Malay News Documents Using Latent Dirichlet Allocation and Sentence Selection Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The proliferation of internet newspapers making an Automatic Text Summarization is now a need to produce a summary that contains most of the important information from the … |
NURAZZAH ABD RAHMAN et. al. | 2021 Fifth International Conference on Information … | 2021-01-01 |
937 | Q^{2}: Evaluating Factual Consistency in Knowledge-Grounded Dialogues Via Question Generation and Question Answering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural knowledge-grounded generative models for dialogue often produce content that is factually inconsistent with the knowledge they rely on, making them unreliable and limiting … |
OR HONOVICH et. al. | ArXiv | 2021-01-01 |
938 | Research on Text Summarization Classification Based on Crowdfunding Projects Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, artificial intelligence technologies represented by deep learning and natural language processing have made huge breakthroughs and have begun to emerge in the … |
Gang Zhou; | MATEC Web of Conferences | 2021-01-01 |
939 | Self-supervised Extractive Text Summarization for Biomedical Literatures Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this study, we propose a self-supervised approach to extractive text summarization for biomedical literature. The approach uses abstracts to find the most informative content … |
Tianyi Xie; Yi Zhen; Tianqi Li; Chuqin Li; Yaorong Ge; | 2021 IEEE 9th International Conference on Healthcare … | 2021-01-01 |
940 | Review of Text Summarization in Indian Regional Languages IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Surendrabikram Thapa; Surabhi Adhikari; Sushruti Mishra; | 2021-01-01 | |
941 | Improving The Readability and Saliency of Abstractive Text Summarization Using Combination of Deep Neural Networks Equipped with Auxiliary Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Rapid and exponential development of textual data in recent years has yielded to the need for automatic text summarization models which aim to automatically condense a piece of … |
Hassan Aliakbarpour; Mohammad Taghi Manzuri; Amir Masoud Rahmani; | The Journal of Supercomputing | 2021-01-01 |
942 | The Impact of Term-weighting Schemes and Similarity Measures on Extractive Multi-document Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is currently a topic of great interest in many knowledge fields. Extractive multi-document text summarization methods aim to reduce the textual … |
Jesús M. Sánchez-Gómez; Miguel A. Vega-Rodríguez; Carlos J. Perez; | Expert Syst. Appl. | 2021-01-01 |
943 | A Discrete Differential Evolution Algorithm for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the exponential growth of textual data on the web, automatic text summarization has become a key task in many natural language processing applications. Many works have been … |
Khadidja Chettah; Amer Draa; | 2021 International Conference on INnovations in Intelligent … | 2021-01-01 |
944 | MyTextSum : Malay Text Summarization Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View |
Suraya Alias; | 2021-01-01 | |
945 | A New Graph-based Extractive Text Summarization Using Keywords or Topic Modeling IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In graph-based extractive text summarization techniques, the weight assigned to the edges of the graph is the crucial parameter for the sentence ranking. The weights associated … |
Ramesh Chandra Belwal; Sawan Rai; Atul Gupta; | J. Ambient Intell. Humaniz. Comput. | 2021-01-01 |
946 | Summary-aware Attention for Social Media Short Text Abstractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural sequence-to-sequence (Seq2Seq) models are currently dominant approaches in social media short text abstractive summarization task. However, the computation of source … |
Qianlong Wang; Jiangtao Ren; | Neurocomputing | 2021-01-01 |
947 | A Study on Tools and Techniques of Big Data Analytics for Text Summarization From Multi-Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multi-document summarization extracts and summarizes the information without affecting its original context from the different sources of documents. It has been carried out using … |
Martin Aruldoss; Miranda Lakshmi Travis; | 2021-01-01 | |
948 | Hybrid Method for Text Summarization Based on Statistical and Semantic Treatment IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization presents several challenges such as considering semantic relationships among words, dealing with redundancy and information diversity issues. Seeking to … |
Nabil Alami; Mostafa El Mallahi; Hicham Amakdouf; Hassan Qjidaa; | Multim. Tools Appl. | 2021-01-01 |
949 | Towards A Knowledge Centric Semantic Approach for Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text Summarization is one of the important process for extracting important data from a text document. In the proposed method, the useful text or data collected is obtained as … |
Siddhant Singh; Gerard Deepak; | 2021-01-01 | |
950 | Practical Machine Learning in JavaScript: TensorFlow.js for Web Developers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: ive text summarization, 102 Application programming interfaces (APIs), 300–301 Artificial intelligence, 2 Attention deficit hyperactivity disorder (ADHD), 95 Audio data accessing … |
Charlie Gerard; | Practical Machine Learning in JavaScript | 2021-01-01 |
951 | A Combined Extractive With Abstractive Model for Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aiming at the difficulties in document-level summarization, this paper presents a two-stage, extractive and then abstractive summarization model. In the first stage, we extract … |
Wenfeng Liu; Yaling Gao; Jinming Li; Yuzhen Yang; | IEEE Access | 2021-01-01 |
952 | Tweet-aware News Summarization with Dual-Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural models have been applied to many text summarization tasks recently. In general, a large number of high quality reference summaries are required to train well-performing … |
Xin Zheng; Aixin Sun; Karthik Muthuswamy; | Companion Proceedings of the Web Conference 2021 | 2021-01-01 |
953 | Evolutionary Algorithm Based Summarization for Analyzing COVID-19 Medical Reports Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The COVID-19 pandemic emerged in the month of December from the very popular city Wuhan of China and spread rapidly all over the country. The present situation depicts the … |
Chirantana Mallick; Sunanda Das; Asit Kumar Das; | Understanding COVID-19: The Role of Computational … | 2021-01-01 |
954 | Discourse-Aware Unsupervised Summarization for Long Scientific Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: We propose an unsupervised graph-based ranking model for extractive summarization of long scientific documents. Our method assumes a two-level hierarchical graph representation of … |
Yue Dong; Andrei Mircea; Jackie C. K. Cheung; | 2021-01-01 | |
955 | Knowledge-based Sentence Semantic Similarity: Algebraical Properties Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Determining the extent to which two text snippets are semantically equivalent is a well-researched topic in the areas of natural language processing, information retrieval and … |
Mourad Oussalah; Muhidin Mohamed; | Progress in Artificial Intelligence | 2021-01-01 |
956 | SE4ExSum: An Integrated Semantic-aware Neural Approach with Graph Convolutional Network for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, advanced techniques in deep learning such as recurrent neural network (GRU, LSTM and Bi-LSTM) and auto-encoding (attention-based transformer and BERT) have achieved … |
Tham Vo; | ACM Trans. Asian Low Resour. Lang. Inf. Process. | 2021-01-01 |
957 | MultiHumES: Multilingual Humanitarian Dataset for Extractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: When responding to a disaster, humanitarian experts must rapidly process large amounts of secondary data sources to derive situational awareness and guide decision-making. While … |
Jenny Paola Yela-Bello; Ewan Oglethorpe; Navid Rekabsaz; | 2021-01-01 | |
958 | Automatic Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Chengqing Zong; Rui Xia; Jiajun Zhang; | 2021-01-01 | |
959 | Abstractive Text Summarization for Hungarian Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In our research we have created a text summarization software tool for Hungarian using multilingual and Hungarian BERT-based models. Two types of text summarization method exist: … |
Zijian Győző Yang; Ádám Agócs; Gábor Kusper; Tamás Váradi; | Applied Medical Informaticvs | 2021-01-01 |
960 | Extractive Summarization Considering Discourse and Coreference Relations Based on Heterogeneous Graph Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Modeling the relations between text spans in a document is a crucial yet challenging problem for extractive summarization. Various kinds of relations exist among text spans of … |
Yin Jou Huang; Sadao Kurohashi; | 2021-01-01 | |
961 | Text Summarization Using Extractive Techniques for Indian Language Related Papers Related Patents Related Grants Related Venues Related Experts View |
Manasi Chouk; Neelam Phadnis; | International Journal of Computer Trends and Technology | 2021-01-01 |
962 | A Graph-Based Opinion Mining Approach for Reducing Information Loss and Overload in Product Reviews Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Information overload is a real challenge that product designers face whiles trying to glean insight from online product reviews. Opinion summaries are limited in the richness of … |
Michael Y. Kpiebaareh; Wei-Ping Wu; Charles R. Haruna; Lawrence Tandoh; Brighter Agyemang; | 2021 The 5th International Conference on Compute and Data … | 2021-01-01 |
963 | A Review Paper on Automatic Text Summarization in Indonesia Language Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is one problem in natural language processing that generates a brief version of the original document. This research took attention for some researchers in this … |
Nurul Khotimah; Adi Wibowo P; Bryan Andreas; Abba Suganda Girsang; | International Journal of Emerging Technology and Advanced … | 2021-01-01 |
964 | Abstractive Text Summarization Using Deep Learning with A New Turkish Summarization Benchmark Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View |
Fatih Ertam; Galip Aydin; | Concurrency and Computation: Practice and Experience | 2021-01-01 |
965 | Automatic Text Summarization Using Deep Reinforcement Learning and Beyond Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the era of big data, information overload problems are becoming increasingly prominent. It is challengingfor machines to understand, compress and filter massive text … |
Gang Sun; Zhongxin Wang; Jia Zhao; | Inf. Technol. Control. | 2021-01-01 |
966 | Designing and Development of Stemmer of Dogri Using Unsupervised Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Stemming and lemmatization are two significant natural language processing techniques that are extensively used in morphological analyzers and are also used in information … |
Parul Gupta; Shubhnandan S. Jamwal; | Soft Computing for Intelligent Systems | 2021-01-01 |
967 | A Bengali Text Summarization Using Encoder-Decoder Based on Social Media Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is one of the strategies of compressing a long document to create a version of the main points of the original text. Due to the excessive amount of long posts … |
FATEMA AKTER FOUZIA et. al. | Advances in Intelligent Systems and Computing | 2021-01-01 |
968 | A Framework for Extractive Text Summarization Based on Deep Learning Modified Neural Network Classifier IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: There is an exponential growth of text data over the internet, and it is expected to gain significant growth and attention in the coming years. Extracting meaningful insights from … |
BALAANAND MUTHU et. al. | Transactions on Asian and Low-Resource Language Information … | 2021-01-01 |
969 | Comparison of Data Augmentation Methods in Pointer-Generator Model Using Various Sentence Ranking Methods Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Currently, the amount of information on the Internet is expected to increase at an average annual rate of 29% from 2010 to 2024, reaching 143 ZB by 2024 [1]. In terms of text … |
Tomohito Ouchi; Masayoshi Tabuse; | 2021-01-01 | |
970 | An Extractive Text Summarization Approach Using Tagged-LDA Based Topic Modeling IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is an exertion of contriving the abridged form of a text document covering salient knowledge. Numerous statistical, linguistic, rule-based, and … |
Ruby Rani; D. K. Lobiyal; | Multim. Tools Appl. | 2021-01-01 |
971 | Regulation TL;DR: Adversarial Text Summarization of Federal Register Articles Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Short on time with a reduced attention span, people disengage from reading long text with a too long, didn’t read justification. While a useful heuristic of managing reading … |
Filipo Sharevski; Peter Jachim; Emma Pieroni; | Proceedings of the 3rd Workshop on Cyber-Security Arms Race | 2021-01-01 |
972 | Jointly Learning Salience and Redundancy By Adaptive Sentence Reranking for Extractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive text summarization seeks to extract indicative sentences from a source document and assemble them to form a summary. Selecting salient but not redundant sentences has … |
Ximing Zhang; Ruifang Liu; | 2021-01-01 | |
973 | Text Summarization Using Extractive and Abstractive Methods Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text Summarization is a process where a huge text file is converted into summarized version which will preserve the original meaning and context. The main aim of any text … |
Saurabh Varade; Ejaaz Sayyed; Vaibhavi Nagtode; Shilpa Shinde; | ITM Web of Conferences | 2021-01-01 |
974 | Learning-Free Unsupervised Extractive Summarization Model IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is an information condensation technique that abbreviates a source document to a few representative sentences with the intention to create a coherent summary … |
Myeongjun Jang; Pilsung Kang; | IEEE Access | 2021-01-01 |
975 | End-to-End AMR Coreference Resolution Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Although parsing to Abstract Meaning Representation (AMR) has become very popular and AMR has been shown effective on the many sentence-level downstream tasks, little work has … |
Qiankun Fu; Linfeng Song; Wenyu Du; Yue Zhang; | 2021-01-01 | |
976 | An Amplified Approach Towards Text Summarization Blueprint Using Python Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sahil Rahman; | International Journal for Research in Applied Science and … | 2021-01-01 |
977 | A Comparative Study of Abstractive and Extractive Summarization Techniques to Label Subgroups on Patent Dataset IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Patents are an important source of information for measuring the technological advancement of a specific knowledge domain. To facilitate the search for information in patent … |
Cinthia Mikaela de Souza; Magali R. G. Meireles; Paulo Eduardo Maciel de Almeida; | Scientometrics | 2021-01-01 |
978 | SumPubMed: Summarization Dataset of PubMed Scientific Articles Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Most earlier work on text summarization is carried out on news article datasets. The summary in these datasets is naturally located at the beginning of the text. Hence, a model … |
Vivek Gupta; Prerna Bharti; Pegah Nokhiz; Harish Karnick; | 2021-01-01 | |
979 | Unsupervised Document Summarization Using Pre-trained Sentence Embeddings and Graph Centrality Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper describes our submission for the LongSumm task in SDP 2021. We propose a method for incorporating sentence embeddings produced by deep language models into extractive … |
Juan Ramirez-Orta; Evangelos Milios; | 2021-01-01 | |
980 | CNLP-NITS @ LongSumm 2021: TextRank Variant for Generating Long Summaries Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The huge influx of published papers in the field of machine learning makes the task of summarization of scholarly documents vital, not just to eliminate the redundancy but also to … |
Darsh Kaushik; Abdullah Faiz Ur Rahman Khilji; Utkarsh Sinha; Partha Pakray; | 2021-01-01 | |
981 | Determination of Text Summary Using Morphological Filtering of Intuitionistic Fuzzy Hypergraph Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text Summarization has been an area of interest for many years. It refers to creating a concise text of a document without any lose of information. Researchers in the area of … |
Dhanya Prabhasadanam Mohanan; Sreekumar Ananda Rao; Jathavedan Madambi; Ramkumar Padinjarepizharath Balakrishna; | Current Topics on Mathematics and Computer Science Vol. 11 | 2021-01-01 |
982 | Android Application for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Purpose The purpose of this study is to provide an automatic text summarization experience using the extractive method within an application implemented on Android. … |
Ayi Hardiyanto; Devi Fitrianah; | Library Hi Tech News | 2021-01-01 |
983 | A NEW MODEL ON AUTOMATIC TEXT SUMMARIZATION FOR TURKISH Related Papers Related Patents Related Grants Related Venues Related Experts View |
Salih BAL; Efnan ŞORA GÜNAL; | Eskişehir Technical University Journal of Science and … | 2021-01-01 |
984 | TS-GAN with Policy Gradient for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Nobel Dang; Ashish Khanna; Viswanatha Reddy Allugunti; | 2021-01-01 | |
985 | Attention Based Abstractive Summarization of Malayalam Document Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: There are different textual content summarization processes available in natural Language Processing. Amongst them abstractive textual content summarization is one of the … |
Sindhya K Nambiar; David Peter S; Sumam Mary Idicula; | Procedia Computer Science | 2021-01-01 |
986 | Feasibility of Using Attention Mechanism in Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Prevalence of information and its magnitude mandates a short description of the core of a document, an article, or legal documents. Abstractive summarization helps to concur … |
Rashed Z. AlMazrouei; Jenophia Nelci; Said A. Salloum; Khaled Shaalan; | Proceedings of International Conference on Emerging … | 2021-01-01 |
987 | Big Data Full-Text Search Index Minimization Using Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An efficient full-text search is achieved by indexing the raw data with an additional 20 to 30 percent storagecost. In the context of Big Data, this additional storage space is … |
Waheed Iqbal; Waqas Ilyas Malik; Faisal Bukhari; Khaled Mohamad Almustafa; Zubiar Nawaz; | Inf. Technol. Control. | 2021-01-01 |
988 | Sentiment Lossless Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The aim of automatic text summarization (ATS) is to extract representative texts from documents and keep major points of the extracted texts consistent with the original … |
Xiaodong Li; Pangjing Wu; Chenxin Zou; Haoran Xie; Fu Lee Wang; | Knowl. Based Syst. | 2021-01-01 |
989 | Sentiment-oriented Query-focused Text Summarization Addressed with A Multi-objective Optimization Approach Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jesus M. Sanchez-Gomez; Miguel A. Vega-Rodríguez; Carlos J. Pérez; | Applied Soft Computing | 2021-01-01 |
990 | Text Summary Augmentation for Intelligent Reading Assistant Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper presents a technique to assist a reader. We aim to reduce manual efforts of the reader by leveraging the state-of-the-art document summarization techniques and … |
Pramod Vadiraja; Andreas Dengel; Shoya Ishimaru; | Augmented Humans Conference 2021 | 2021-01-01 |
991 | Multi-document Extractive Text Summarization Based on Firefly Algorithm IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extracting relevant information from a large amount of data is a challenging task. Automatic text summarization is a potential solution for obtaining this information. In this … |
Minakshi Tomer; Manoj Kumar; | Journal of King Saud University – Computer and Information … | 2021-01-01 |
992 | Preserve Integrity in Realtime Event Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Online text streams such as Twitter are the major information source for users when they are looking for ongoing events. Realtime event summarization aims to generate and update … |
Chen Lin; Zhichao Ouyang; Xiaoli Wang; Hui Li; Zhenhua Huang; | ACM Transactions on Knowledge Discovery from Data (TKDD) | 2021-01-01 |
993 | Leveraging DistilBERT for Summarizing Arabic Text: An Extractive Dual-Stage Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Towards tackling the phenomenon of textual information overload that is exponentially pumping with redundancy over the Internet, this paper investigates a solution depending on … |
ABDULLAH ALSHANQITI et. al. | IEEE Access | 2021-01-01 |
994 | A Survey on Abstractive Summarization Models Using Machine Learning and Deep Learning Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive Summarization models has gained popularity in past few years especially Sequential Models with attention. With the rise in data summarizing data is of utmost … |
Varun Jain; Rejo Mathew; | Social Science Research Network | 2021-01-01 |
995 | Hybrid Model For Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text Summarization is a method to reduce a huge text into a meaningful condensed form. Today’s era is technological era. The people are always in the need of instant information … |
Sujata Kolhe; Poonam Patil; | SSRN Electronic Journal | 2021-01-01 |
996 | Improving Abstractive Summarization Based on Dynamic Residual Network with Reinforce Dependency IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Seq2Seq abstract summarization model based on long short-term memory (LSTM) is very effective for short text summarization. However, LSTM is limited by long-term dependencies, … |
Weizhi Liao; Yaheng Ma; Yanchao Yin; Guanglei Ye; Dongzhou Zuo; | Neurocomputing | 2021-01-01 |
997 | Unsupervised Summarization Approach With Computational Statistics of Microblog Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Microblogging, where millions of users exchange messages to share their opinions on different trending and non-trending topics, is one of the popular communication media in recent … |
ABHISHEK BHATTACHARYA et. al. | 2021-01-01 | |
998 | ElmNet: A Benchmark Dataset for Generating Headlines from Persian Papers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Headline generation is a challenging subtask of abstractive text summarization, which its output should be a summary, shorter than one sentence. It would be precious to develop a … |
Mohammad E. Shenassa; Behrouz Minaei-Bidgoli; | Multimedia Tools and Applications | 2021-01-01 |
999 | Automatic Text Summarization Using Genetic Algorithm and Repetitive Patterns Related Papers Related Patents Related Grants Related Venues Related Experts View |
EBRAHIM HEIDARY et. al. | Cmc-computers Materials & Continua | 2021-01-01 |
1000 | Comparative Analysis of Tamil and English News Text Summarization Using Text Rank Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The exponential growth of newsgroups has made it more difficult to gain accurate access to a large amount of data. To deal with the massive amounts of data, efficient and … |
M Sarika; | 2021-01-01 | |
1001 | Abstractive Summarization Using Categorical Graph Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid development of technologies produce enormous amount of data which have lot of hidden insights. Extracting these hidden insights are challengeable for researchers and … |
Senthamizh Selvan R; | Revista Gestão Inovação e Tecnologias | 2021-01-01 |
1002 | Hybrid Algorithm Based on Chicken Swarm Optimization and Genetic Algorithm for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mostafa Gamal; Ahmed El-Sawy; Ahmed AbuEl-Atta; | International Journal of Intelligent Engineering and Systems | 2021-01-01 |
1003 | PunKtuator: A Multilingual Punctuation Restoration System for Spoken and Written Text Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Text transcripts without punctuation or sentence boundaries are hard to comprehend for both humans and machines. Punctuation marks play a vital role by providing meaning to the … |
Varnith Chordia; | 2021-01-01 | |
1004 | A Comparative Study on Abstractive and Extractive Approaches in Summarization of European Legislation Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extracting the most important part of legislation documents has great business value because the texts are usually very long and hard to understand. The aim of this article is to … |
Valentin Zmiycharov; Milen Chechev; Gergana Lazarova; Todor Tsonkov; Ivan Koychev; | 2021-01-01 | |
1005 | Topic Modeling Combined with Classification Technique for Extractive Multi-document Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The qualities of human readable summaries available in the datasets are not up to the mark, leading to issues in creating an accurate model for text summarization. Although recent … |
Rajendra Kumar Roul; | Soft Comput. | 2021-01-01 |
1006 | A Deep Neural Architecture Based Meta-review Generation and Final Decision Prediction of A Scholarly Article Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Peer reviews form an essential part of scientific communications. Research papers and proposals are reviewed by several peers before they are finally accepted or rejected for … |
Tribikram Pradhan; Chaitanya Bhatia; Prashant Kumar; Sukomal Pal; | Neurocomputing | 2021-01-01 |
1007 | Text Summarization Based on Multi-head Self-attention Mechanism and Pointer Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Existing text summarization methods mainly rely on the mapping between manually labeled standard summaries and the original text for feature extraction, often ignoring the … |
Dong Qiu; Bing Yang; | Complex & Intelligent Systems | 2021-01-01 |
1008 | Deep Learning Based On Different Methods For Text Summary: A Survey IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstract—in today’s rapidly growing information age, text summary has become a critical and important instrument for help understanding text information. it is really hard for … |
Saja Naeem Turky; Ahmed Sabah Ahmed AL-Jumaili; Rajaa K. Hasoun; | 2021-01-01 | |
1009 | Improving Unsupervised Extractive Summarization with Facet-Aware Modeling Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unsupervised extractive summarization aims to extract salient sentences from documents without labeled corpus. Existing methods are mostly graph-based by computing sentence … |
Xinnian Liang; Shuangzhi Wu; Mu Li; Zhoujun Li; | 2021-01-01 | |
1010 | Particle Swarm Optimization for Punjabi Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Particle swarm optimization (PSO) algorithm is proposed to deal with text summarization for the Punjabi language. PSO is based on intelligence that predicts among a given set of … |
Arti Jain; Divakar Yadav; Anuja Arora; | International Journal of Operations Research and … | 2021-01-01 |
1011 | Performance-Driven Reinforcement Learning Approach for Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Trang-Phuong N. Nguyen; Nam-Chi Van; Nhi-Thao Tran; | 2021-01-01 | |
1012 | Translating Sentimental Statements Using Deep Learning Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Natural Language Processing (NLP) allows machines to know nature languages and helps us do tasks, such as retrieving information, answering questions, text summarization, … |
Yin-Fu Huang; Yi-Hao Li; | Electronics | 2021-01-01 |
1013 | BarChartAnalyzer: Digitizing Images of Bar Charts IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Charts or scientific plots are widely used visualizations for efficient knowledge dissemination from datasets. However, these charts are predominantly available in image format. … |
Komal Dadhich; Siri Chandana Daggubati; Jaya Sreevalsan-Nair; | 2021-01-01 | |
1014 | Correction To: Arabic Text Summarization Using Deep Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An amendment to this paper has been published and can be accessed via the original article. … |
Molham Al-Maleh; Said Desouki; | Journal of Big Data | 2021-01-01 |
1015 | Overview of The MEDIQA 2021 Shared Task on Summarization in The Medical Domain Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The MEDIQA 2021 shared tasks at the BioNLP 2021 workshop addressed three tasks on summarization for medical text: (i) a question summarization task aimed at exploring new … |
ASMA BEN ABACHA et. al. | 2021-01-01 | |
1016 | Arabic Text Summarization Via Knapsack Balancing of Effective Retention Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper presents a new extractive Arabic text summarization approach based on the Knapsack balancing of effective retention. Effective retention refers to maximizing retention … |
Alaidine Ben Ayed; Ismaïl Biskri; Jean-Guy Meunier; | Procedia Computer Science | 2021-01-01 |
1017 | Named Entity Recognition on Software Requirements Specification Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Software Requirements Specifications (SRS) documents set the requirements and expectations of software development projects. This textual information is considered as a guideline … |
Garima Malik; Mucahit Cevik; Yusef Khedr; Devang Parikh; Ayşe Başar; | Proceedings of the Canadian Conference on Artificial … | 2021-01-01 |
1018 | An Automated Bengali Text Summarization Technique Using Lexicon-Based Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: There is enough resources for English to process and obtain summarize documents. But this thing is not directly applicable for Bengali language as there is lots of complexity in … |
BUSRAT JAHAN et. al. | 2021-01-01 | |
1019 | Somun: Entity-centric Summarization Incorporating Pre-trained Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization resolves the issue of capturing essential information from a large volume of text data. Existing methods either depend on the end-to-end models or hand-crafted … |
Emrah Inan; | Neural Computing and Applications | 2021-01-01 |
1020 | A Case Study on User Evaluation of Scientific Publication Summarization By Japanese Students Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summaries of scientific publications enable readers to gain an overview of a large number of studies, but users’ preferences have not yet been explored. In this paper, we conduct … |
Shintaro Yamamoto; Ryota Suzuki; Tsukasa Fukusato; Hirokatsu Kataoka; Shigeo Morishima; | Applied Sciences | 2021-01-01 |
1021 | Unsupervised Derivation of Keyword Summary for Short Texts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatically summarizing a group of short texts that mainly share one topic is a fundamental task in many applications, e.g., summarizing the main symptoms for a disease based on … |
BIN CAO et. al. | ACM Transactions on Internet Technology (TOIT) | 2021-01-01 |
1022 | Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In light of this, we explore parameter-sharing methods in Transformers with a specific focus on generative models. |
Machel Reid; Edison Marrese-Taylor; Yutaka Matsuo; | arxiv-cs.CL | 2021-01-01 |
1023 | Extractive-Abstractive Summarization of Judgment Documents Using Multiple Attention Networks Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yan Gao; Zhengtao Liu; Juan Li; Fan Guo; Fei Xiao; | 2021-01-01 | |
1024 | Extractive Summarization of Chinese Judgment Documents Via Sentence Embedding and Memory Network Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yan Gao; Zhengtao Liu; Juan Li; Jin Tang; | 2021-01-01 | |
1025 | Extractive Text Summerization Pada Berita Berbahasa Indonesia Menggunakan Algoritma Support Vector Machine Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: According to the Program for International Student Assessment (PISA) for the 2018 survey of 61 countries that participated in PISA, the reading interest of the Indonesian people … |
Thalita Meisya Permata Aulia; Asep Jamaludin; Tesa Nur Padilah; | 2021-01-01 | |
1026 | Automatic Summarization of New Testament Exegesis Texts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper we present two algorithms that can be used for EATS (Extractive Automatic Text Summarization) of theological New Testament exegesis texts. Both algorithms represent … |
Daniel-Avram Pop; Adrian Sterca; | 2021 International Conference on INnovations in Intelligent … | 2021-01-01 |
1027 | Automatic Persian Text Summarization Using Linguistic Features from Text Structure Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ebrahim Heidary; Ham飀 Parv飊; Samad Nejatian; Karamollah Bagherifard; Vahideh Rezaie; | Computers, Materials & Continua | 2021-01-01 |
1028 | A Graph-to-Sequence Learning Framework for Summarizing Opinionated Texts IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: There is a great need for effective summarization methods to absorb the key points of large amounts of opinions expressed on the Web. In this paper, we study the problem of … |
Penghui Wei; Jiahao Zhao; Wenji Mao; | IEEE/ACM Transactions on Audio, Speech, and Language … | 2021-01-01 |
1029 | Crowdsourced Social Media Reaction Analysis for Recommendation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A pre-analysis is always important for crucial decision making in many events where reviews, feedback, and comments posted by different stakeholders play an important role. … |
Jaiprakash Vinodkumar Verma; Sudeep Tanwar; Sanjay Garg; Abhay Dinesh Rathod; | Int. J. Knowl. Syst. Sci. | 2021-01-01 |
1030 | Salience Estimation and Faithful Generation: Modeling Methods for Text Summarization and Generation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Christopher Kedzie; | 2021-01-01 | |
1031 | Otomatisasi Peringkasan Teks Pada Dokumen Hukum Menggunakan Metode Latent Semantic Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: At present, the number of crimes in Indonesia is quite large. The large number of crimes in Indonesia will have an impact on the number of legal documents that will be handled by … |
Millenia Rusbandi; Imam Fahrur Rozi; Kadek Suarjuna Batubulan; | Jurnal Informatika Polinema | 2021-01-01 |
1032 | Abstractive Text Summarization on Templatized Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive text summarization generates a brief form of an input text from the original source without the sentences being reused by still preserving the meaning and the … |
C. Jyothi; M. Supriya; | 2021-01-01 | |
1033 | Myanmar News Summarization Using Different Word Representations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: There is enormous amount information available in different forms of sources and genres. In order to extract useful information from a massive amount of data, automatic mechanism … |
Soe Soe Lwin; Khin Thandar Nwet; | International Journal of Electrical and Computer Engineering | 2021-01-01 |
1034 | An Evaluation of Automatic Text Summarization of News Articles: The Case of Three Online Arabic Text Summary Generators Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Digital news platforms and online newspapers have multiplied at an unprecedented speed, making it difficult for users to read and follow all news articles on important, relevant … |
Fahad M. Alliheibi; Abdulfattah Omar; Nasser Al-Horais; | International Journal of Advanced Computer Science and … | 2021-01-01 |
1035 | An Automatic Abstractive Text Summarization Model Based on Hybrid Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Attentional sequence-to-sequence models based on RNN have achieved promising performances in the automatic abstractive summarization technology. However, there are still some … |
Zhe Wang; | Journal of Physics: Conference Series | 2021-01-01 |
1036 | On-Device Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With increasing connectivity, there has been an exponential surge in the creation and availability of textual content in the form of news articles, blogs, social media posts and … |
Mehak Preet Dhaliwal; Rishabh Kumar; Mukund Rungta; Hemant Tiwari; Vanraj Vala; | 2021 IEEE 15th International Conference on Semantic … | 2021-01-01 |
1037 | Enhancing Summarization with Text Classification Via Topic Consistency Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The recent success of abstractive summarization is partly due to the availability of large-volume and high-quality human-produced summaries for training, which are extremely … |
Jingzhou Liu; Yiming Yang; | 2021-01-01 | |
1038 | Information Extraction Tasks Based on BERT and SpaCy on Tourism Domain Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we present two methodologies to extract particular information based on the full text returned from the search engine to facilitate the users. The approaches are … |
Chantana Chantrapornchai; Aphisit Tunsakul; | 2021-01-01 | |
1039 | Extractive Summarization Based on Dynamic Memory Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We present an extractive summarization model based on the Bert and dynamic memory network. The model based on Bert uses the transformer to extract text features and uses the … |
Ping Li; Jiong Yu; | Symmetry | 2021-01-01 |
1040 | Abstraction Based Bengali Text Summarization Using Bi-directional Attentive Recurrent Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summarizing text is recognized as a vital problem in the field of deep learning and natural language processing (NLP). The entire process of text summarization is proved to be … |
Md. Muhaiminul Islam; Mohiyminul Islam; Abu Kaisar Mohammad Masum; Sheikh Abujar; Syed Akhter Hossain; | 2021-01-01 | |
1041 | Towards Explainable AI: Assessing The Usefulness and Impact of Added Explainability Features in Legal Document Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study tested two different approaches for adding an explainability feature to the implementation of a legal text summarization solution based on a Deep Learning (DL) model. … |
Milda Norkute; Nadja Herger; Leszek Michalak; Andrew Mulder; Sally Gao; | Extended Abstracts of the 2021 CHI Conference on Human … | 2021-01-01 |
1042 | A Survey of Text Summarization Approaches Based on Deep Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization (ATS) has achieved impressive performance thanks to recent advances in deep learning (DL) and the availability of large-scale corpora. The key points … |
SHENG-LUAN HOU et. al. | Journal of Computer Science and Technology | 2021-01-01 |
1043 | SQL Injection Vulnerability Identification from Text Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Increasing usage of Information Technology (IT) applications in distributed environment is leading to an increase in security exploits. Vulnerabilities related information is also … |
Dhruv Parashar; Lalit Mohan Sanagavarapu; Y. Raghu Reddy; | 14th Innovations in Software Engineering Conference … | 2021-01-01 |
1044 | Unsupervised Query-focused Multi-document Summarization Based on Transfer Learning from Sentence Embedding Models, BM25 Model, and Maximal Marginal Relevance Criterion IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive query-focused multi-document summarization (QF-MDS) is the process of automatically generating an informative summary from a collection of documents that answers a … |
Salima Lamsiyah; Abdelkader El Mahdaouy; Said Ouatik El Alaoui; Bernard Espinasse; | Journal of Ambient Intelligence and Humanized Computing | 2021-01-01 |
1045 | SKGSUM: Abstractive Document Summarization with Semantic Knowledge Graphs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In abstractive single-document summarization task, generated summaries always suffer from fabricated and less informative content. An intuitive way to alleviate this problem is to … |
Xin Ji; Wen Zhao; | 2021 International Joint Conference on Neural Networks … | 2021-01-01 |
1046 | Biomedical Text Summarization: A Graph-Based Ranking Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The latest and precise information regarding the biomedical and healthcare domain is required in the current pandemic situation. The world has turned into a small place where … |
Supriya Gupta; Aakanksha Sharaff; Naresh Kumar Nagwani; | Advances in Intelligent Systems and Computing | 2021-01-01 |
1047 | FCN-LectureNet: Extractive Summarization of Whiteboard and Chalkboard Lecture Videos IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recording and sharing of educational or lecture videos has increased in recent years. Within these recordings, we find a large number of math-oriented lectures and tutorials which … |
Kenny Davila; Fei Xu; Srirangaraj Setlur; Venu Govindaraju; | IEEE Access | 2021-01-01 |
1048 | The Automatic Question Generation System for CET Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we apply the abstractive text summarization technology to automatic generation system of reading comprehension, which is part of College English Test (CET) in … |
Xinya Zhang; Xiaodong Yan; Zhou Yao; | Journal of Computer and Communications | 2021-01-01 |
1049 | SUMDocS: Surrounding-aware Unsupervised Multi-Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multi-document summarization, which summarizes a set of documents with a small number of phrases or sentences, provides a concise and critical essence of the documents. Existing … |
Qi Zhu; Fang Guo; Jingjing Tian; Yuning Mao; Jiawei Han; | 2021-01-01 | |
1050 | Survey on Automatic Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Journal of Computer Research and Development | 2021-01-01 | |
1051 | Automatic Generation of The Draft Procuratorial Suggestions Based on An Extractive Summarization Method: BERTSLCA Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The automatic generation of the draft procuratorial suggestions is to extract the description of illegal facts, administrative omission, description of laws and regulations, and … |
Yufeng Sun; Fengbao Yang; Xiaoxia Wang; Hongsong Dong; | Mathematical Problems in Engineering | 2021-01-01 |
1052 | A Joint Model for Structure-based News Genre Classification with Application to Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Journalists usually organize and present the contents of a news article following a welldefined structure. In this paper, we propose a novel joint model for structure-based news … |
Zeyu Dai; Ruihong Huang; | 2021-01-01 | |
1053 | Text Summarization of Multiple Documents Using Binary Fruit Fly Optimization Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the availability of huge data on the Internet, it becomes a time-consuming process for the user to find the most relevant text related to their interesting topic. This … |
Kishore Kumar Mamidala; Suresh Kumar Sanampudi; | Lecture Notes in Networks and Systems | 2021-01-01 |
1054 | A Heuristic Approach for Telugu Text Summarization with Improved Sentence Ranking Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extracting/abstracting the condensed form of original text document by retaining its information and complete meaning is known as text summarization. The creation of manual … |
Kishore Kumar Mamidala Et.al; | 2021-01-01 | |
1055 | Frame Semantics Guided Network for Abstractive Sentence Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive Text Summarization is an important and practical task, aiming to rephrase the input text into a short version summary, while preserving its same and important … |
Yong Guan; Shaoru Guo; Ru Li; Xiaoli Li; Hu Zhang; | Knowl. Based Syst. | 2021-01-01 |
1056 | A Two-stage Chinese Text Summarization Algorithm Using Keyword Information and Adversarial Learning IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: At present, most Chinese text summarization algorithms use the sequence-to-sequence model, but this model is prone to the problems of unknown words and incomplete content … |
Zhenrong Deng; Ma Fuxin; Rushi Lan; Wenming Huang; Xiaonan Luo; | Neurocomputing | 2021-01-01 |
1057 | TEXT SUMMARIZATION WITH SENTIMENTAL ANALYSIS Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In today’s world, Modern organizations deal with terabytes of text, such as email, that often plays a significant role in their day to day operations. The user has to face a task … |
Kummari Shiva Kumar; M Priyanka; M Rishitha; D Divya Teja; Nallamothu Madhuri; | International Journal of Innovative Research in Computer … | 2021-01-01 |
1058 | Heterogeneous Graph Based Extractive Summarization Considering Discourse and Coreference Relations Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yin Jou Huang; Sadao Kurohashi; | 2021-01-01 | |
1059 | An Approach to Generate The Bug Report Summaries Using Two-level Feature Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Bug report is one of the major software artifact which is generated during the software development process. Changing requirements in the software development process leads to the … |
Som Gupta; Sanjai Kumar Gupta; | Expert Syst. Appl. | 2021-01-01 |
1060 | Weakly Supervised Extractive Summarization with Attention Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic summarization aims to extract important information from large amounts of textual data in order to create a shorter version of the original texts while preserving its … |
Yingying Zhuang; Yichao Lu; Simi Wang; | SIGDIAL Conferences | 2021-01-01 |
1061 | Extractive Text Summarization Using Recent Approaches: A Survey Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: ive Models for Long Text Summarization, 2017 [21] Machine Learning Approach, Evaluation metric used ROUGE (RN, R-L) Sentence extraction, Summary generation In this paper evaluated … |
Avaneesh Kumar Yadav; Ashish Kumar Maurya; Rama Shankar Yadav; | Ingénierie des Systèmes d Inf. | 2021-01-01 |
1062 | HITS-based Attentional Neural Model for Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic abstractive summary generation is still an open problem in natural language processing field Conventional encoder–decoder model based abstractive summarization methods … |
Xiaoyan Cai; Kaile Shi; Yuehan Jiang; Libin Yang; Sen Liu; | Knowl. Based Syst. | 2021-01-01 |
1063 | A Semantic Supervision Method for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
SUNQIANG HU et. al. | Cmc-computers Materials & Continua | 2021-01-01 |
1064 | Extractive Single Document Summarization Using Multi-objective modified Cat Swarm Optimization Approach: ESDS-MCSO Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As the world is progressing faster, to compete with the demand, the need for proficient computing technology has increased, resulting in huge volumes of data. Consequently, the … |
Dipanwita Debnath; Ranjita Das; Partha Pakray; | Neural Computing and Applications | 2021-01-01 |
1065 | Improving Deep Learning Based Multi-document Summarization Through Linguistic Knowledge Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multi-document summarization is one of the most important tasks in the field of Natural Language Processing (NLP) and it gains increasing attention in recent years. It aims to … |
Congbo Ma; | Proceedings of the 44th International ACM SIGIR Conference … | 2021-01-01 |
1066 | Extractive Text Summarization Using Recurrent Neural Networks with Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive summarization aims to select the most important sentences or words from a document to generate a summary. Traditional summarization approaches have relied extensively … |
Shimirwa Aline Valerie; | Advances in Machine Learning | 2021-01-01 |
1067 | User Query-Based Automatic Text Summarization of Web Documents Using Ontology Related Papers Related Patents Related Grants Related Venues Related Experts View |
K. Selvakumar; L. Sairamesh; | 2021-01-01 | |
1068 | Extractive Summarization of EHR Notes Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ajay Chaudhary; Merlin George; Anu Mary Chacko; | 2021-01-01 | |
1069 | CtnR: Compress-then-Reconstruct Approach for Multimodal Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the rapid growth of multimodal data in social medias and the huge requirement of short but abundant information. Multimodal summarization has drawn much attention in both … |
Chenxi Zhang; Zijian Zhang; Jiangfeng Li; Qin Liu; Hongming Zhu; | 2021 International Joint Conference on Neural Networks … | 2021-01-01 |
1070 | A Survey of The State-of-the-Art Models in Neural Abstractive Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Dealing with vast amounts of textual data requires the use of efficient systems. Automatic summarization systems are capable of addressing this issue. Therefore, it becomes highly … |
Ayesha Ayub Syed; Ford Lumban Gaol; Tokuro Matsuo; | IEEE Access | 2021-01-01 |
1071 | Fine-Tuned T5 for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Abdul Ghafoor Etemad; Ali Imam Abidi; Megha Chhabra; | Int. J. Perform. Eng. | 2021-01-01 |
1072 | Automatic Text Summarization of COVID-19 Research Articles Using Recurrent Neural Networks and Coreference Resolution Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Purpose: Pandemic COVID-19 has created an emergency for the medical community. Researchers require extensive study of scientific literature in order to discover drugs and … |
Mahsa Afsharizadeh; Hossein Ebrahimpour-Komleh; Ayoub Bagheri; | 2021-01-01 | |
1073 | PE-MSC: Partial Entailment-based Minimum Set Cover for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Anand Gupta; Manpreet Kaur; Sonaali Mittal; Swati Garg; | Knowl. Inf. Syst. | 2021-01-01 |
1074 | Text Summarization Technique for Punjabi Language Using Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the contemporary world, utilization of digital content has risen exponentially. For example, newspaper and web articles, status updates, advertisements etc. have become an … |
Arti Jain; Anuja Arora; Divakar Yadav; Jorge Morato; Amanpreet Kaur; | Int. Arab J. Inf. Technol. | 2021-01-01 |
1075 | A Gist Information Guided Neural Network for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yawei Kong; Lu Zhang; Can Ma; | 2021-01-01 | |
1076 | Complementary Representation of ALBERT for Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Wenying Guo; | Proceedings of the 33rd International Conference on … | 2021-01-01 |
1077 | Research on Chinese Text Summarization Based on Core Word Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The neural sequence-to-sequence model provides a feasible new method for abstract text summarization.Because the traditional Seq2Seq neural network model only judges the … |
Wenxiang Xu; Caiquan Xiong; Huasong Cheng; | 2021 16th International Conference on Computer Science & … | 2021-01-01 |
1078 | Redundancy Removal Method for Multi-Document Query-Based Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We present RedunWSD, a Word Sense Disambiguation (WSD) based redundancy removal method for multiple text documents query-based text summarization. Recognizing and identifying the … |
Nazreena Rahman; Bhogeswar Borah; | 2021 International Symposium on Electrical, Electronics and … | 2021-01-01 |
1079 | Identifying Implicit Quotes for Unsupervised Extractive Summarization for Conversational Texts Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ryuji Kano; Tomoki Taniguchi; Tomoko Ohkuma; | 2021-01-01 | |
1080 | UCSD-Adobe at MEDIQA 2021: Transfer Learning and Answer Sentence Selection for Medical Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we describe our approach to question summarization and multi-answer summarization in the context of the 2021 MEDIQA shared task (Ben Abacha et al., 2021). We … |
KHALIL MRINI et. al. | 2021-01-01 | |
1081 | UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper describes a system developed to summarize multiple answers challenge in the MEDIQA 2021 shared task collocated with the BioNLP 2021 Workshop. We propose an extractive … |
DUY-CAT CAN et. al. | 2021-01-01 | |
1082 | IBMResearch at MEDIQA 2021: Toward Improving Factual Correctness of Radiology Report Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Although recent advances in abstractive summarization systems have achieved high scores on standard natural language metrics like ROUGE, their lack of factual consistency remains … |
Diwakar Mahajan; Ching-Huei Tsou; Jennifer J Liang; | 2021-01-01 | |
1083 | MNLP at MEDIQA 2021: Fine-Tuning PEGASUS for Consumer Health Question Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper details a Consumer Health Question (CHQ) summarization model submitted to MEDIQA 2021 for shared task 1: Question Summarization. Many CHQs are composed of multiple … |
Jooyeon Lee; Huong Dang; Özlem Uzuner; Sam Henry; | 2021-01-01 | |
1084 | BiDETS: Binary Differential Evolutionary Based Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In extraction-based automatic text summarization (ATS) applications, feature scoring is the cornerstone of the summarization process since it is used for selecting the candidate … |
Hani Moetque Aljahdali; Ahmed Hamza; Albaraa Abuobieda; | International Journal of Advanced Computer Science and … | 2021-01-01 |
1085 | Optum at MEDIQA 2021: Abstractive Summarization of Radiology Reports Using Simple BART Finetuning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper describes experiments undertaken and their results as part of the BioNLP MEDIQA 2021 challenge. We participated in Task 3: Radiology Report Summarization. Multiple runs … |
Ravi Kondadadi; Sahil Manchanda; Jason Ngo; Ronan McCormack; | 2021-01-01 | |
1086 | UETfishes at MEDIQA 2021: Standing-on-the-Shoulders-of-Giants Model for Abstractive Multi-answer Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper describes a system developed to summarize multiple answers challenge in the MEDIQA 2021 shared task collocated with the BioNLP 2021 Workshop. We present an abstractive … |
HOANG-QUYNH LE et. al. | 2021-01-01 | |
1087 | Monitoring Fact Preservation, Grammatical Consistency and Ethical Behavior of Abstractive Summarization Neural Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The paper describes a system for automatic summarization in English language of online news data that come from different non-English languages. The system is designed to be used … |
IVA MARINOVA et. al. | 2021-01-01 | |
1088 | Single Document Text Summarization Technique Using Optimal Combination of Cuckoo Search Algorithm, Sentence Scoring and Sentiment Score Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shrabanti Mandal; Girish Kumar Singh; Anita Pal; | International Journal of Information Technology | 2021-01-01 |
1089 | An Efficacious Text Summarization Process Using Triple Encoding-Decoding Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As the big data and internet growing huge day by day, there is in need to overwhelm people by the information in large. These kind of issues makes researchers to create a … |
V. D. Ambeth Kumar; R. SubhaShini; K. Priyanka; | Advances in Parallel Computing | 2021-01-01 |
1090 | An Arabic Multi-source News Corpus: Experimenting on Single-document Extractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is considered as an important task in various fields in natural language processing such as information retrieval. It is a process of automatically … |
Amina Chouigui; Oussama Ben Khiroun; Bilel Elayeb; | Arabian Journal for Science and Engineering | 2021-01-01 |
1091 | Towards Automatically Generating Release Notes Using Extractive Summarization Technique Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View |
Sristy Sumana; | Proceedings of the 33rd International Conference on … | 2021-01-01 |
1092 | Spam Text Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Spam Detection is the process to classify text which contains irrelevant or unsolicited messages sent over the internet, typically to a large number of users, for the purposes of … |
Dharmik Timbadia; Niraj Vesaokar; | International Journal of Scientific Research in Computer … | 2021-01-01 |
1093 | SGATS: Semantic Graph-based Automatic Text Summarization from Hindi Text Documents Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Creating a coherent summary of the text is a challenging task in the field of Natural Language Processing (NLP). Various Automatic Text Summarization techniques have been … |
Manju Lata Joshi; Nisheeth Joshi; Namita Mittal; | ACM Trans. Asian Low Resour. Lang. Inf. Process. | 2021-01-01 |
1094 | Improving Text Summarization Using Feature Extraction Approach Based on Pointer-generator with Coverage Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yongchao Chen; Xin He; Guanghui Wang; Junyang Yu; | 2021-01-01 | |
1095 | Text Summarization Approaches Using Machine Learning & LSTM Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the massive amount of online textual data generated in a diversity of social media, web, and other information-centric applications. To select the vital data from the large … |
Neeraj Kumar Sirohi; Dr. Mamta Bansal; Dr.S.N. Rajan Rajan; | Revista Gestão Inovação e Tecnologias | 2021-01-01 |
1096 | Automatic Text Summarization: A Comprehensive Survey IF:6 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic Text Summarization (ATS) is becoming much more important because of the huge amount of textual content that grows exponentially on the Internet and the various archives … |
Wafaa S. El-Kassas; Cherif R. Salama; Ahmed A. Rafea; Hoda K. Mohamed; | Expert Syst. Appl. | 2021-01-01 |
1097 | Extractive Text Summarization Methods in The Spanish Language Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The quantity of information in the world is increasing every day on a fast level. This fact will be an obstacle in some situations; text summarization is involved in this kind of … |
Irvin Raul Lopez Contreras; Alejandra Mendoza Carreón; Jorge Rodas-Osollo; Martiza Concepción Varela; | 2021-01-01 | |
1098 | Narrative Summarization in The Domain of Finance Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The number of electronic text documents is growing and so is the need for automatic text summarizers. In the financedomain, documents can be quite long, averaging at approximately … |
Samir Abdaljalil; | 2021-01-01 | |
1099 | Text Summarization and Its Types Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is a compressing technique of the original text to form a summary which will provide the same meaning and information as provided by the original version. … |
Namrata Kumari; Pardeep Singh; | 2021-01-01 | |
1100 | Story Summarization Using A Question-Answering Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summarization is the process of selecting representative data to produce a reduced version of the given data with a minimal loss of information; so, it generally works on text, … |
Sanah Nashir Sayyed; Namrata Mahender C.; | 2021-01-01 | |
1101 | TTSD: A Novel Dataset for Turkish Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, with the increase in the amount of data on the internet, it becomes extremely important to collect salient information from these data efficiently. Gathering and … |
Mehtap Ülker; Ahmet Bedri Özer; | 2021 9th International Symposium on Digital Forensics and … | 2021-01-01 |
1102 | Abstractive Summarization with Word Embedding Prediction and Scheduled Sampling Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization models based on the encoder-decoder framework have made great advances over the recent years. Since most summarization datasets only provide a reference … |
Qing Liu; Lei Chen; Yuan Yuan; | 2021 6th International Conference on Automation, Control … | 2021-01-01 |
1103 | Automatic Citation Contextualization Based Scientific Document Summarization Using Multi-objective Differential Evolution Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The wide availability of research articles makes it harder for researchers to quickly learn about the progress made in their respective field’s. However, citation-based scientific … |
Dipanwita Debnath; Ranjita Das; | Advanced Techniques for IoT Applications | 2021-01-01 |
1104 | Abstractive Review Summarization Based on Improved Attention Mechanism with Pointer Generator Network Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays online reviews play an important role by giving an helping hand to the customers to know about other customer’s opinions about the product they are going to purchase. … |
J. Shobana; M. Murali; | 2021-01-01 | |
1105 | Graph-based Multimodal Ranking Models for Multimodal Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Multimodal summarization aims to extract the most important information from the multimedia input. It is becoming increasingly popular due to the rapid growth of multimedia data … |
Junnan Zhu; Lu Xiang; Yu Zhou; Jiajun Zhang; Chengqing Zong; | Transactions on Asian and Low-Resource Language Information … | 2021-01-01 |
1106 | Gated Dynamic Convolutions with Deep Layer Fusion for Abstractive Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We present a novel abstractive document summarization based on the recently proposed dynamic convolutional encoder-decoder architectures. We address several aspects of … |
HONG-SEOK KWON et. al. | Comput. Speech Lang. | 2021-01-01 |
1107 | On Generating Extended Summaries Of Long Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a new method for generating extended summaries of long papers. |
Sajad Sotudeh; Arman Cohan; Nazli Goharian; | arxiv-cs.CL | 2020-12-28 |
1108 | Leveraging ParsBERT And Pretrained MT5 For Persian Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes two methods to address this task and introduces a novel dataset named pn-summary for Persian abstractive text summarization. |
Mehrdad Farahani; Mohammad Gharachorloo; Mohammad Manthouri; | arxiv-cs.CL | 2020-12-21 |
1109 | Multi‐layered Attentional Peephole Convolutional LSTM for Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive text summarization is a process of making a summary of a given text by paraphrasing the facts of the text while keeping the meaning intact. The manmade summary … |
Md Motiur Rahman; Fazlul Hasan Siddiqui; | ETRI Journal | 2020-12-18 |
1110 | Literature Retrieval For Precision Medicine With Neural Matching And Faceted Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a document reranking approach that combines neural query-document matching and text summarization toward such retrieval scenarios. |
Jiho Noh; Ramakanth Kavuluru; | arxiv-cs.CL | 2020-12-16 |
1111 | What Makes A Good and Useful Summary? Incorporating Users in Automatic Summarization Research Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we focus on university students, who make extensive use of summaries during their studies. |
Maartje ter Hoeve; Julia Kiseleva; Maarten de Rijke; | arxiv-cs.CL | 2020-12-14 |
1112 | Contrastive Learning with Adversarial Perturbations for Conditional Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to mitigate the conditional text generation problem by contrasting positive pairs with negative pairs, such that the model is exposed to various valid or incorrect perturbations of the inputs, for improved generalization. |
Seanie Lee; Dong Bok Lee; Sung Ju Hwang; | arxiv-cs.CL | 2020-12-14 |
1113 | Fairness for Whom? Understanding The Reader’s Perception of Fairness in Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the surge in user-generated textual information, there has been a recent increase in the use of summarization algorithms for providing an overview of the extensive content. … |
Anurag Shandilya; A. Dash; Abhijnan Chakraborty; Kripabandhu Ghosh; Saptarshi Ghosh; | 2020 IEEE International Conference on Big Data (Big Data) | 2020-12-10 |
1114 | CTRLsum: Towards Generic Controllable Text Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this limitation, we present CTRLsum, a novel framework for controllable summarization. |
Junxian He; Wojciech Kryściński; Bryan McCann; Nazneen Rajani; Caiming Xiong; | arxiv-cs.CL | 2020-12-08 |
1115 | Cross-lingual Transfer of Abstractive Summarizer to Less-resource Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our work, we use a pre-trained English summarization model based on deep neural networks and sequence-to-sequence architecture to summarize Slovene news articles. |
Aleš Žagar; Marko Robnik-Šikonja; | arxiv-cs.CL | 2020-12-08 |
1116 | Using Multiple ASR Hypotheses To Boost I18n NLU Performance Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We explore the change in performance of NLU associated tasks when utilizing five-best ASR hypotheses when compared to status quo for two language datasets, German and Portuguese. |
CHARITH PERIS et. al. | arxiv-cs.CL | 2020-12-07 |
1117 | An Enhanced MeanSum Method For Generating Hotel Multi-Review Summarizations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The aim of this work was to use Multi-Aspect Masker(MAM) as content selector to address the issue with multi-aspect. |
Saibo Geng; Diego Antognini; | arxiv-cs.CL | 2020-12-07 |
1118 | Bengali Abstractive News Summarization(BANS): A Neural Attention Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this article, we presented a seq2seq based Long Short-Term Memory (LSTM) network model with attention at encoder-decoder. |
Prithwiraj Bhattacharjee; Avi Mallick; Md Saiful Islam; | arxiv-cs.CL | 2020-12-03 |
1119 | Do We Really Need That Many Parameters In Transformer For Extractive Summarization? Discourse Can Help ! IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel parameter-lean self-attention mechanism using discourse priors. |
Wen Xiao; Patrick Huber; Giuseppe Carenini; | arxiv-cs.CL | 2020-12-03 |
1120 | Meta-Embeddings For Natural Language Inference And Semantic Similarity Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to use Meta Embedding derived from few State-of-the-Art (SOTA) models to efficiently tackle mainstream NLP tasks like classification, semantic relatedness, and text similarity. |
Shree Charran R; Rahul Kumar Dubey; | arxiv-cs.CL | 2020-12-01 |
1121 | Fact-level Extractive Summarization With Hierarchical Graph Mask On BERT IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to extract fact-level semantic units for better extractive summarization. |
Ruifeng Yuan; Zili Wang; Wenjie Li; | arxiv-cs.CL | 2020-11-19 |
1122 | ColdGANs: Taming Language GANs with Cautious Sampling Strategies IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show how the most popular sampling method results in unstable training for language GANs. |
Thomas Scialom; Paul-Alexis Dray; Sylvain Lamprier; Benjamin Piwowarski; Jacopo Staiano; | nips | 2020-11-17 |
1123 | Friendly Topic Assistant For Transformer Based Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we rearrange and explore the semantics learned by a topic model, and then propose a topic assistant (TA) including three modules. |
ZHENGJUE WANG et. al. | emnlp | 2020-11-12 |
1124 | Evaluating The Factual Consistency Of Abstractive Text Summarization IF:7 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a weakly-supervised, model-based approach for verifying factual consistency and identifying conflicts between source documents and generated summaries. |
Wojciech Kryscinski; Bryan McCann; Caiming Xiong; Richard Socher; | emnlp | 2020-11-12 |
1125 | PALM: Pre-training An Autoencoding&Autoregressive Language Model For Context-conditioned Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work presents PALM with a novel scheme that jointly pre-trains an autoencoding and autoregressive language model on a large unlabeled corpus, specifically designed for generating new text conditioned on context. |
BIN BI et. al. | emnlp | 2020-11-12 |
1126 | Summarizing Text On Any Aspects: A Knowledge-Informed Weakly-Supervised Approach IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we study summarizing on \textit{arbitrary} aspects relevant to the document, which significantly expands the application of the task in practice. |
Bowen Tan; Lianhui Qin; Eric Xing; Zhiting Hu; | emnlp | 2020-11-12 |
1127 | Adversarial Semantic Collisions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop gradient-based approaches for generating semantic collisions and demonstrate that state-of-the-art models for many tasks which rely on analyzing the meaning and similarity of texts-including paraphrase identification, document retrieval, response suggestion, and extractive summarization-are vulnerable to semantic collisions. |
Congzheng Song; Alexander Rush; Vitaly Shmatikov; | emnlp | 2020-11-12 |
1128 | On Extractive And Abstractive Neural Document Summarization With Transformer Language Models IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a method to produce abstractive summaries of long documents that exceed several thousand words via neural abstractive summarization. |
Jonathan Pilault; Raymond Li; Sandeep Subramanian; Chris Pal; | emnlp | 2020-11-12 |
1129 | MLSUM: The Multilingual Summarization Corpus IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. |
Thomas Scialom; Paul-Alexis Dray; Sylvain Lamprier; Benjamin Piwowarski; Jacopo Staiano; | emnlp | 2020-11-12 |
1130 | Multi-hop Inference For Question-driven Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a novel question-driven abstractive summarization method, Multi-hop Selective Generator (MSG), to incorporate multi-hop reasoning into question-driven summarization and, meanwhile, provide justifications for the generated summaries. |
Yang Deng; Wenxuan Zhang; Wai Lam; | emnlp | 2020-11-12 |
1131 | Text Segmentation By Cross Segment Attention IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose three transformer-based architectures and provide comprehensive comparisons with previously proposed approaches on three standard datasets. |
Michal Lukasik; Boris Dadachev; Kishore Papineni; Gonçalo Simões; | emnlp | 2020-11-12 |
1132 | Multi-Fact Correction In Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address this challenge, we propose Span-Fact, a suite of two factual correction models that leverages knowledge learned from question answering models to make corrections in system-generated summaries via span selection. |
YUE DONG et. al. | emnlp | 2020-11-12 |
1133 | Re-evaluating Evaluation In Text Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we make an attempt to re-evaluate the evaluation method for text summarization: assessing the reliability of automatic metrics using top-scoring system outputs, both abstractive and extractive, on recently popular datasets for both system-level and summary-level evaluation settings. |
Manik Bhandari; Pranav Narayan Gour; Atabak Ashfaq; Pengfei Liu; Graham Neubig; | emnlp | 2020-11-12 |
1134 | TESA: A Task In Entity Semantic Aggregation For Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a new dataset and task aimed at the semantic aggregation of entities. |
Clément Jumel; Annie Louis; Jackie Chi Kit Cheung; | emnlp | 2020-11-12 |
1135 | Multi-View Sequence-to-Sequence Models With Conversational Structure For Abstractive Dialogue Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work proposes a multi-view sequence-to-sequence model by first extracting conversational structures of unstructured daily chats from different views to represent conversations and then utilizing a multi-view decoder to incorporate different views to generate dialogue summaries. |
Jiaao Chen; Diyi Yang; | emnlp | 2020-11-12 |
1136 | Stepwise Extractive Summarization And Planning With Structured Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose encoder-centric stepwise models for extractive summarization using structured transformers – HiBERT and Extended Transformers. |
SHASHI NARAYAN et. al. | emnlp | 2020-11-12 |
1137 | Pre-training For Abstractive Document Summarization By Reinstating Source Text IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents three sequence-to-sequence pre-training (in shorthand, STEP) objectives which allow us to pre-train a SEQ2SEQ based abstractive summarization model on unlabeled text. |
Yanyan Zou; Xingxing Zhang; Wei Lu; Furu Wei; Ming Zhou; | emnlp | 2020-11-12 |
1138 | Improving Text Generation With Student-Forcing Optimal Transport IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To reduce this gap between training and testing, we propose using optimal transport (OT) to match the sequences generated in these two modes. |
JIANQIAO LI et. al. | emnlp | 2020-11-12 |
1139 | Neural Extractive Summarization With Hierarchical Attentive Heterogeneous Graph Network IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose HAHSum (as shorthand for Hierarchical Attentive Heterogeneous Graph for Text Summarization), which well models different levels of information, including words and sentences, and spotlights redundancy dependencies between sentences. |
RUIPENG JIA et. al. | emnlp | 2020-11-12 |
1140 | Understanding Neural Abstractive Summarization Models Via Uncertainty IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we analyze summarization decoders in both blackbox and whitebox ways by studying on the entropy, or uncertainty, of the model’s token-level predictions. |
Jiacheng Xu; Shrey Desai; Greg Durrett; | emnlp | 2020-11-12 |
1141 | What Have We Achieved On Text Summarization? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Aiming to gain more understanding of summarization systems with respect to their strengths and limits on a fine-grained syntactic and semantic level, we consult the Multidimensional Quality Metric (MQM) and quantify 8 major sources of errors on 10 representative summarization models manually. |
DANDAN HUANG et. al. | emnlp | 2020-11-12 |
1142 | Conditional Neural Generation Using Sub-Aspect Functions For Extractive News Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a neural framework that can flexibly control summary generation by introducing a set of sub-aspect functions (i.e. importance, diversity, position). |
Zhengyuan Liu; Ke Shi; Nancy Chen; | emnlp | 2020-11-10 |
1143 | TED: A Pretrained Unsupervised Summarization Model With Theme Modeling And Denoising IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to address these issues, we propose TED, a transformer-based unsupervised abstractive summarization system with pretraining on large-scale data. |
ZIYI YANG et. al. | emnlp | 2020-11-10 |
1144 | ProphetNet: Predicting Future N-gram For Sequence-to-Sequence Pre-training IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a new sequence-to-sequence pre-training model called ProphetNet, which introduces a novel self-supervised objective named future n-gram prediction and the proposed n-stream self-attention mechanism. |
WEIZHEN QI et. al. | emnlp | 2020-11-10 |
1145 | A Hierarchical Network For Abstractive Meeting Summarization With Cross-Domain Pretraining IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel abstractive summary network that adapts to the meeting scenario. |
Chenguang Zhu; Ruochen Xu; Michael Zeng; Xuedong Huang; | emnlp | 2020-11-10 |
1146 | WikiLingua: A New Benchmark Dataset For Multilingual Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce WikiLingua, a large-scale, multilingual dataset for the evaluation of cross-lingual abstractive summarization systems. |
Faisal Ladhak; Esin Durmus; Claire Cardie; Kathleen McKeown; | emnlp | 2020-11-10 |
1147 | Document Reranking For Precision Medicine With Neural Matching And Faceted Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a document reranking approach that combines neural query-document matching and text summarization toward such retrieval scenarios. |
Jiho Noh; Ramakanth Kavuluru; | emnlp | 2020-11-10 |
1148 | Unsupervised Extractive Summarization By Pre-training Hierarchical Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we find that transformer attentions can be used to rank sentences for unsupervised extractive summarization. |
Shusheng Xu; Xingxing Zhang; Yi Wu; Furu Wei; Ming Zhou; | emnlp | 2020-11-10 |
1149 | An Empirical Study Of Cross-Dataset Evaluation For Neural Summarization Systems IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we perform an in-depth analysis of characteristics of different datasets and investigate the performance of different summarization models under a cross-dataset setting, in which a summarizer trained on one corpus will be evaluated on a range of out-of-domain corpora. |
YIRAN CHEN et. al. | emnlp | 2020-11-10 |
1150 | KLearn: Background Knowledge Inference From Summarization Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Building on the realization that the choices made by human summarizers and annotators contain implicit information about their background knowledge, we develop and compare techniques for inferring background knowledge from summarization data. |
Maxime Peyrard; Robert West; | emnlp | 2020-11-10 |
1151 | Abstractive Multi-Document Summarization Via Joint Learning With Single-Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to improve neural abstractive multi-document summarization by jointly learning an abstractive single-document summarizer. |
Hanqi Jin; Xiaojun Wan; | emnlp | 2020-11-10 |
1152 | Adversarial Semantic Collisions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop gradient-based approaches for generating semantic collisions and demonstrate that state-of-the-art models for many tasks which rely on analyzing the meaning and similarity of texts– including paraphrase identification, document retrieval, response suggestion, and extractive summarization– are vulnerable to semantic collisions. |
Congzheng Song; Alexander M. Rush; Vitaly Shmatikov; | arxiv-cs.CL | 2020-11-09 |
1153 | Automatic Summarization Of Open-Domain Podcast Episodes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present implementation details of our abstractive summarizers that achieve competitive results on the Podcast Summarization task of TREC 2020. |
Kaiqiang Song; Chen Li; Xiaoyang Wang; Dong Yu; Fei Liu; | arxiv-cs.CL | 2020-11-08 |
1154 | Metrics Also Disagree In The Low Scoring Range: Revisiting Summarization Evaluation Metrics IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we revisit their experiments and find that their observations stem from the fact that metrics disagree in ranking summaries from any narrow scoring range. |
Manik Bhandari; Pranav Gour; Atabak Ashfaq; Pengfei Liu; | arxiv-cs.CL | 2020-11-08 |
1155 | Detecting Hallucinated Content in Conditional Neural Sequence Generation IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To detect these errors, we propose a task to predict whether each token in the output sequence is hallucinated (not contained in the input) and collect new manually annotated evaluation sets for this task. |
CHUNTING ZHOU et. al. | arxiv-cs.CL | 2020-11-04 |
1156 | WSL-DS: Weakly Supervised Learning With Distant Supervision For Query Focused Multi-Document Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To overcome this issue, in this paper, we propose a novel weakly supervised learning approach via utilizing distant supervision. |
Md Tahmid Rahman Laskar; Enamul Hoque; Jimmy Xiangji Huang; | arxiv-cs.CL | 2020-11-02 |
1157 | Liputan6: A Large-scale Indonesian Dataset For Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a large-scale Indonesian summarization dataset. |
Fajri Koto; Jey Han Lau; Timothy Baldwin; | arxiv-cs.CL | 2020-11-01 |
1158 | Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce a novel and generalizable method, called WikiTransfer, for fine-tuning pretrained models for summarization in an unsupervised, dataset-specific manner. |
ALEXANDER R. FABBRI et. al. | arxiv-cs.CL | 2020-10-24 |
1159 | Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Constrained Abstractive Summarization (CAS), a general setup that preserves the factual consistency of abstractive summarization by specifying tokens as constraints that must be present in the summary. |
Yuning Mao; Xiang Ren; Heng Ji; Jiawei Han; | arxiv-cs.CL | 2020-10-23 |
1160 | Learning To Summarize Long Texts With Memory Compression And Transfer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce Mem2Mem, a memory-to-memory mechanism for hierarchical recurrent neural network based encoder decoder architectures and we explore its use for abstractive document summarization. |
Jaehong Park; Jonathan Pilault; Christopher Pal; | arxiv-cs.CL | 2020-10-21 |
1161 | Topic-Guided Abstractive Text Summarization: A Joint Learning Approach Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a new approach for abstractive text summarization, Topic-Guided Abstractive Summarization, which calibrates long-range dependencies from topic-level features with globally salient content. |
Chujie Zheng; Kunpeng Zhang; Harry Jiannan Wang; Ling Fan; Zhe Wang; | arxiv-cs.CL | 2020-10-20 |
1162 | DistilSum:: Distilling The Knowledge for Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce DistilSum, which contains teacher mechanism and student model. |
RUIPENG JIA et. al. | cikm | 2020-10-19 |
1163 | Generating Categories for Sets of Entities Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To aid knowledge editors in the manual process of expanding a category system, this paper presents a method of generating categories for sets of entities. |
Shuo Zhang; Krisztian Balog; Jamie Callan; | cikm | 2020-10-19 |
1164 | SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we describe our text summarization system, SciSummPip, inspired by SummPip (Zhao et al., 2020) that is an unsupervised text summarization system for multi-document in news domain. |
Jiaxin Ju; Ming Liu; Longxiang Gao; Shirui Pan; | arxiv-cs.CL | 2020-10-18 |
1165 | Factual Error Correction for Abstractive Summarization Models IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a post-editing corrector module to address this issue by identifying and correcting factual errors in generated summaries. |
Meng Cao; Yue Dong; Jiapeng Wu; Jackie Chi Kit Cheung; | arxiv-cs.CL | 2020-10-17 |
1166 | Lexicon-constrained Copying Network for Chinese Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To solve this problem, we propose a lexicon-constrained copying network that models multi-granularity in both encoder and decoder. |
Boyan Wan; Mishal Sohail; | arxiv-cs.CL | 2020-10-16 |
1167 | MAST: Multimodal Abstractive Summarization With Trimodal Hierarchical Attention IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents MAST, a new model for Multimodal Abstractive Text Summarization that utilizes information from all three modalities — text, audio and video — in a multimodal video. |
Aman Khullar; Udit Arora; | arxiv-cs.CL | 2020-10-15 |
1168 | Multi-Task Learning For Cross-Lingual Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a multi-task learning framework for cross-lingual abstractive summarization to augment training data. Recent studies constructed pseudo cross-lingual abstractive summarization data to train their neural encoder-decoders. Meanwhile, we introduce existing genuine data such as translation pairs and monolingual abstractive summarization data into training. |
Sho Takase; Naoaki Okazaki; | arxiv-cs.CL | 2020-10-15 |
1169 | Re-evaluating Evaluation In Text Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we make an attempt to re-evaluate the evaluation method for text summarization: assessing the reliability of automatic metrics using top-scoring system outputs, both abstractive and extractive, on recently popular datasets for both system-level and summary-level evaluation settings. |
Manik Bhandari; Pranav Gour; Atabak Ashfaq; Pengfei Liu; Graham Neubig; | arxiv-cs.CL | 2020-10-14 |
1170 | Enhancing Extractive Text Summarization With Topic-Aware Graph Neural Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address these issues, this paper proposes a graph neural network (GNN)-based extractive summarization model, enabling to capture inter-sentence relationships efficiently via graph-structured document representation. |
Peng Cui; Le Hu; Yuanchao Liu; | arxiv-cs.CL | 2020-10-13 |
1171 | Summarizing Text On Any Aspects: A Knowledge-Informed Weakly-Supervised Approach IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we study summarizing on arbitrary aspects relevant to the document, which significantly expands the application of the task in practice. |
Bowen Tan; Lianhui Qin; Eric P. Xing; Zhiting Hu; | arxiv-cs.CL | 2020-10-13 |
1172 | Improving Text Generation With Student-Forcing Optimal Transport IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To reduce this gap between training and testing, we propose using optimal transport (OT) to match the sequences generated in these two modes. |
GUOYIN WANG et. al. | arxiv-cs.CL | 2020-10-12 |
1173 | Context-Aware Multi-View Summarization Network For Image-Text Matching IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Toward this end, we present a novel context-aware multi-view summarization network to summarize context-enhanced visual region information from multiple views. |
Leigang Qu; Meng Liu; Da Cao; Liqiang Nie; Qi Tian; | mm | 2020-10-12 |
1174 | CDEvalSumm: An Empirical Study Of Cross-Dataset Evaluation For Neural Summarization Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we perform an in-depth analysis of characteristics of different datasets and investigate the performance of different summarization models under a cross-dataset setting, in which a summarizer trained on one corpus will be evaluated on a range of out-of-domain corpora. |
YIRAN CHEN et. al. | arxiv-cs.CL | 2020-10-10 |
1175 | Mark-Evaluate: Assessing Language Generation Using Population Estimation Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a family of metrics to assess language generation derived from population estimation methods widely used in ecology. |
Gonçalo Mordido; Christoph Meinel; | arxiv-cs.CL | 2020-10-09 |
1176 | Automatic Generation Of Reviews Of Scientific Papers Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a method for the automatic generation of a review paper corresponding to a user-defined query. |
Anna Nikiforovskaya; Nikolai Kapralov; Anna Vlasova; Oleg Shpynov; Aleksei Shpilman; | arxiv-cs.LG | 2020-10-08 |
1177 | A Cascade Approach To Neural Abstractive Summarization With Content Selection And Fusion IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present an empirical study in favor of a cascade architecture to neural text summarization. |
Logan Lebanoff; Franck Dernoncourt; Doo Soon Kim; Walter Chang; Fei Liu; | arxiv-cs.CL | 2020-10-07 |
1178 | WikiLingua: A New Benchmark Dataset For Cross-Lingual Abstractive Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce WikiLingua, a large-scale, multilingual dataset for the evaluation of crosslingual abstractive summarization systems. |
Faisal Ladhak; Esin Durmus; Claire Cardie; Kathleen McKeown; | arxiv-cs.CL | 2020-10-06 |
1179 | SupMMD: A Sentence Importance Model For Extractive Summarization Using Maximum Mean Discrepancy Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present SupMMD, a novel technique for generic and update summarization based on the maximum mean discrepancy from kernel two-sample testing. |
Umanga Bista; Alexander Patrick Mathews; Aditya Krishna Menon; Lexing Xie; | arxiv-cs.CL | 2020-10-06 |
1180 | Stepwise Extractive Summarization And Planning With Structured Transformers IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose encoder-centric stepwise models for extractive summarization using structured transformers — HiBERT and Extended Transformers. |
SHASHI NARAYAN et. al. | arxiv-cs.CL | 2020-10-06 |
1181 | Reducing Quantity Hallucinations In Abstractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It is well-known that abstractive summaries are subject to hallucination—including material that is not supported by the original text. While summaries can be made … |
Zheng Zhao; Shay B. Cohen; Bonnie Webber; | arxiv-cs.CL | 2020-09-28 |
1182 | XTE: Explainable Text Entailment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce XTE – Explainable Text Entailment – a novel composite approach for recognizing text entailment which analyzes the entailment pair to decide whether it must be resolved syntactically or semantically. |
Vivian S. Silva; André Freitas; Siegfried Handschuh; | arxiv-cs.CL | 2020-09-25 |
1183 | Persian Keyphrase Generation Using Sequence-to-Sequence Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we try to tackle the problem of keyphrase generation and extraction from news articles using deep sequence-to-sequence models. |
Ehsan Doostmohammadi; Mohammad Hadi Bokaei; Hossein Sameti; | arxiv-cs.CL | 2020-09-25 |
1184 | PerKey: A Persian News Corpus For Keyphrase Extraction And Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce PerKey, a corpus of 553k news articles from six Persian news websites and agencies with relatively high quality author extracted keyphrases, which is then filtered and cleaned to achieve higher quality keyphrases. |
Ehsan Doostmohammadi; Mohammad Hadi Bokaei; Hossein Sameti; | arxiv-cs.CL | 2020-09-25 |
1185 | Extracting Summary Knowledge Graphs from Long Documents IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a new text-to-graph task of predicting summarized knowledge graphs from long documents. We develop a dataset of 200k document/graph pairs using automatic and human annotations. |
Zeqiu Wu; Rik Koncel-Kedziorski; Mari Ostendorf; Hannaneh Hajishirzi; | arxiv-cs.CL | 2020-09-19 |
1186 | Looking Beyond Sentence-Level Natural Language Inference For Downstream Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study this unfulfilled promise from the lens of two downstream tasks: question answering (QA), and text summarization. |
ANSHUMAN MISHRA et. al. | arxiv-cs.CL | 2020-09-18 |
1187 | Noisy Self-Knowledge Distillation for Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we apply self-knowledge distillation to text summarization which we argue can alleviate problems with maximum-likelihood training on single reference and noisy datasets. |
Yang Liu; Sheng Shen; Mirella Lapata; | arxiv-cs.CL | 2020-09-15 |
1188 | MultiGBS: A Multi-layer Graph Approach to Biomedical Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a domain-specific method that models a document as a multi-layer graph to enable multiple features of the text to be processed at the same time. |
Ensieh Davoodijam; Nasser Ghadiri; Maryam Lotfi Shahreza; Fabio Rinaldi; | arxiv-cs.IR | 2020-08-27 |
1189 | Generating (Factual?) Narrative Summaries Of RCTs: Experiments With Neural Multi-Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose new approaches that capitalize on domain-specific models to inform summarization, e.g., by explicitly demarcating snippets of inputs that convey key findings, and emphasizing the reports of large and high-quality trials. |
Byron C. Wallace; Sayantan Saha; Frank Soboczenski; Iain J. Marshall; | arxiv-cs.CL | 2020-08-25 |
1190 | A Baseline Analysis For Podcast Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a baseline analysis of podcast summarization using the Spotify Podcast Dataset provided by TREC 2020. |
Chujie Zheng; Harry Jiannan Wang; Kunpeng Zhang; Ling Fan; | arxiv-cs.CL | 2020-08-24 |
1191 | Abstractive Summarization Of Spoken And Written Instructions With BERT IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our work presents the first application of the BERTSum model to conversational language. |
Alexandra Savelieva; Bryan Au-Yeung; Vasanth Ramani; | arxiv-cs.CL | 2020-08-21 |
1192 | Experiments In Extractive Summarization: Integer Linear Programming, Term/Sentence Scoring, And Title-driven Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we revisit the challenging problem of unsupervised single-document summarization and study the following aspects: Integer linear programming (ILP) based algorithms, Parameterized normalization of term and sentence scores, and Title-driven approaches for summarization. |
Daniel Lee; Rakesh Verma; Avisha Das; Arjun Mukherjee; | arxiv-cs.IR | 2020-07-31 |
1193 | Leverage Unlabeled Data For Abstractive Speech Summarization With Self-Supervised Learning And Back-Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a French meeting summarization task where reports are predicted based on the automatic transcription of the meeting audio recordings. |
PAUL TARDY et. al. | arxiv-cs.CL | 2020-07-30 |
1194 | Evaluation Of Cross Domain Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We examined two state-of-the-art hybrid summarization algorithms from three novel perspectives: we applied them to a form of headline generation not previously tried, we evaluated the generalization of the algorithms by testing them both within and across news domains; and we compared the automatic assessment of the algorithms to human comparative judgments. |
Liam Scanlon; Shiwei Zhang; Xiuzhen Zhang; Mark Sanderson; | sigir | 2020-07-25 |
1195 | Extractive Snippet Generation For Arguments IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce the task of generating a snippet that represents the main claim and reason of an argument. |
Milad Alshomary; Nick Düsterhus; Henning Wachsmuth; | sigir | 2020-07-25 |
1196 | Large Scale Abstractive Multi-Review Summarization (LSARS) Via Aspect Alignment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the first large-scale abstractive multi-review summarization dataset that leverages more than 17.9 billion raw reviews and uses novel aspect-alignment techniques based on aspect annotations. |
HAOJIE PAN et. al. | sigir | 2020-07-25 |
1197 | SummEval: Re-evaluating Summarization Evaluation IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We address the existing shortcomings of summarization evaluation methods along five dimensions: 1) we re-evaluate 14 automatic evaluation metrics in a comprehensive and consistent fashion using neural summarization model outputs along with expert and crowd-sourced human annotations, 2) we consistently benchmark 23 recent summarization models using the aforementioned automatic evaluation metrics, 3) we assemble the largest collection of summaries generated by models trained on the CNN/DailyMail news dataset and share it in a unified format, 4) we implement and share a toolkit that provides an extensible and unified API for evaluating summarization models across a broad range of automatic metrics, 5) we assemble and share the largest and most diverse, in terms of model types, collection of human judgments of model-generated summaries on the CNN/Daily Mail dataset annotated by both expert judges and crowd-source workers. |
ALEXANDER R. FABBRI et. al. | arxiv-cs.CL | 2020-07-24 |
1198 | ERNIE-GEN: An Enhanced Multi-Flow Pre-training And Fine-tuning Framework For Natural Language Generation IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this issue, we propose an enhanced multi-flow sequence to sequence pre-training and fine-tuning framework named ERNIE-GEN, which bridges the discrepancy between training and inference with an infilling generation mechanism and a noise-aware generation method. |
DONGLING XIAO et. al. | ijcai | 2020-07-21 |
1199 | From Standard Summarization To New Tasks And Beyond: Summarization With Manifold Information IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on the survey of these new summarization tasks and approaches in the real-world application. |
Shen Gao; Xiuying Chen; Zhaochun Ren; Dongyan Zhao; Rui Yan; | ijcai | 2020-07-21 |
1200 | Hierarchical Interaction Networks with Rethinking Mechanism for Document-level Sentiment Analysis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we study how to effectively generate a discriminative representation with explicit subject patterns and sentiment contexts for DSA. |
LINGWEI WEI et. al. | arxiv-cs.CL | 2020-07-16 |
1201 | Align Then Summarize: Automatic Alignment Methods For Summarization Corpus Creation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Using a bootstrapping approach, we provide pre-alignments that are corrected by human annotators, making a validation set against which we evaluate automatic models. |
Paul Tardy; David Janiszek; Yannick Estève; Vincent Nguyen; | arxiv-cs.CL | 2020-07-15 |
1202 | Sequence Generation with Mixed Representations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose to leverage the mixed representations from different tokenization methods for sequence generation tasks, in order to boost the model performance with unique characteristics and advantages of individual tokenization methods. |
LIJUN WU et. al. | icml | 2020-07-11 |
1203 | PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization IF:8 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose pre-training large Transformer-based encoder-decoder models on massive text corpora with a new self-supervised objective. |
Jingqing Zhang; Yao Zhao; Mohammad Saleh; Peter Liu; | icml | 2020-07-11 |
1204 | Time-aware Large Kernel Convolutions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce Time-aware Large Kernel (TaLK) Convolutions, a novel adaptive convolution operation that learns to predict the size of a summation kernel instead of using a fixed-sized kernel matrix. |
Vasileios Lioutas; Yuhong Guo; | icml | 2020-07-11 |
1205 | Advances Of Transformer-Based Models For News Headline Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we fine-tune two pretrained Transformer-based models (mBART and BertSumAbs) for that task and achieve new state-of-the-art results on the RIA and Lenta datasets of Russian news. |
Alexey Bukhtiyarov; Ilya Gusev; | arxiv-cs.CL | 2020-07-09 |
1206 | Continual BERT: Continual Learning For Adaptive Extractive Summarization Of COVID-19 Literature IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To aid the community in understanding the rapidly flowing array of COVID-19 literature, we propose a novel BERT architecture that provides a brief yet original summarization of lengthy papers. |
Jong Won Park; | arxiv-cs.CL | 2020-07-07 |
1207 | A Deep Reinforced Model For Zero-Shot Cross-Lingual Summarization With Bilingual Semantic Similarity Rewards Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose an end-to-end cross-lingual text summarization model. |
Zi-Yi Dou; Sachin Kumar; Yulia Tsvetkov; | arxiv-cs.CL | 2020-06-27 |
1208 | Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel architecture that extends Transformer encoder-decoder architecture in order to improve on these shortcomings. |
Beliz Gunel; Chenguang Zhu; Michael Zeng; Xuedong Huang; | arxiv-cs.CL | 2020-06-27 |
1209 | Evaluation of Text Generation: A Survey IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: For each category, we discuss the progress that has been made and the challenges still being faced, with a focus on the evaluation of recently proposed NLG tasks and neural NLG models. |
Asli Celikyilmaz; Elizabeth Clark; Jianfeng Gao; | arxiv-cs.CL | 2020-06-26 |
1210 | Graph Optimal Transport For Cross-Domain Alignment IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose Graph Optimal Transport (GOT), a principled framework that germinates from recent advances in Optimal Transport (OT). |
LIQUN CHEN et. al. | arxiv-cs.CL | 2020-06-25 |
1211 | Discourse-Aware Neural Extractive Text Summarization IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address these issues, we present a discourse-aware neural summarization model – DiscoBert. |
Jiacheng Xu; Zhe Gan; Yu Cheng; Jingjing Liu; | acl | 2020-06-20 |
1212 | Unsupervised Opinion Summarization With Noising And Denoising IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we enable the use of supervised learning for the setting where there are only documents available (e.g., product or business reviews) without ground truth summaries. |
Reinald Kim Amplayo; Mirella Lapata; | acl | 2020-06-20 |
1213 | Knowledge Graph-Augmented Abstractive Summarization With Semantic-Driven Cloze Reward IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present ASGARD, a novel framework for Abstractive Summarization with Graph-Augmentation and semantic-driven RewarD. |
Luyang Huang; Lingfei Wu; Lu Wang; | acl | 2020-06-20 |
1214 | Optimizing The Factual Correctness Of A Summary: A Study Of Summarizing Radiology Reports IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we develop a general framework where we evaluate the factual correctness of a generated summary by fact-checking it automatically against its reference using an information extraction module. |
Yuhao Zhang; Derek Merck; Emily Tsai; Christopher D. Manning; Curtis Langlotz; | acl | 2020-06-20 |
1215 | Multi-Granularity Interaction Network For Extractive And Abstractive Multi-Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a multi-granularity interaction network for extractive and abstractive multi-document summarization, which jointly learn semantic representations for words, sentences, and documents. |
Hanqi Jin; Tianming Wang; Xiaojun Wan; | acl | 2020-06-20 |
1216 | Facet-Aware Evaluation For Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a facet-aware evaluation setup for better assessment of the information coverage in extracted summaries. |
Yuning Mao; Liyuan Liu; Qi Zhu; Xiang Ren; Jiawei Han; | acl | 2020-06-20 |
1217 | Extractive Summarization As Text Matching IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper creates a paradigm shift with regard to the way we build neural extractive summarization systems. |
MING ZHONG et. al. | acl | 2020-06-20 |
1218 | Self-Attention Guided Copy Mechanism For Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a Transformer-based model to enhance the copy mechanism. |
SONG XU et. al. | acl | 2020-06-20 |
1219 | Improving Truthfulness Of Headline Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper explores improving the truthfulness in headline generation on two popular datasets. |
Kazuki Matsumaru; Sho Takase; Naoaki Okazaki; | acl | 2020-06-20 |
1220 | Composing Elementary Discourse Units In Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we argue that elementary discourse unit (EDU) is a more appropriate textual unit of content selection than the sentence unit in abstractive summarization. |
Zhenwen Li; Wenhao Wu; Sujian Li; | acl | 2020-06-20 |
1221 | Attend To Medical Ontologies: Content Selection For Clinical Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we approach the content selection problem for clinical abstractive summarization by augmenting salient ontological terms into the summarizer. |
Sajad Sotudeh Gharebagh; Nazli Goharian; Ross Filice; | acl | 2020-06-20 |
1222 | Storytelling With Dialogue: A Critical Role Dungeons And Dragons Dataset IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes the Critical Role Dungeons and Dragons Dataset (CRD3) and related analyses. |
Revanth Rameshkumar; Peter Bailey; | acl | 2020-06-20 |
1223 | On Faithfulness And Factuality In Abstractive Summarization IF:7 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we have analyzed limitations of these models for abstractive document summarization and found that these models are highly prone to hallucinate content that is unfaithful to the input document. |
Joshua Maynez; Shashi Narayan; Bernd Bohnet; Ryan McDonald; | acl | 2020-06-20 |
1224 | Asking And Answering Questions To Evaluate The Factual Consistency Of Summaries IF:6 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose QAGS (pronounced kags), an automatic evaluation protocol that is designed to identify factual inconsistencies in a generated summary. |
Alex Wang; Kyunghyun Cho; Mike Lewis; | acl | 2020-06-20 |
1225 | Screenplay Summarization Using Latent Narrative Structure IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose to explicitly incorporate the underlying structure of narratives into general unsupervised and supervised extractive summarization models. |
Pinelopi Papalampidi; Frank Keller; Lea Frermann; Mirella Lapata; | acl | 2020-06-20 |
1226 | Heterogeneous Graph Neural Networks For Extractive Document Summarization IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a heterogeneous graph-based neural network for extractive summarization (HETERSUMGRAPH), which contains semantic nodes of different granularity levels apart from sentences. |
Danqing Wang; Pengfei Liu; Yining Zheng; Xipeng Qiu; Xuanjing Huang; | acl | 2020-06-20 |
1227 | FEQA: A Question Answering Evaluation Framework For Faithfulness Assessment In Abstractive Summarization IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We tackle the problem of evaluating faithfulness of a generated summary given its source document. |
Esin Durmus; He He; Mona Diab; | acl | 2020-06-20 |
1228 | Leveraging Graph To Improve Abstractive Multi-Document Summarization IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we develop a neural abstractive multi-document summarization (MDS) model which can leverage well-known graph representations of documents such as similarity graph and discourse graph, to more effectively process multiple input documents and produce abstractive summaries. |
WEI LI et. al. | acl | 2020-06-20 |
1229 | Dataset for Automatic Summarization of Russian News IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We describe the properties of this dataset and benchmark several extractive and abstractive models. |
Ilya Gusev; | arxiv-cs.CL | 2020-06-19 |
1230 | SEAL: Segment-wise Extractive-Abstractive Long-form Text Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we study long-form abstractive text summarization, a sequence-to-sequence setting with input sequence lengths up to 100,000 tokens and output sequence lengths up to 768 tokens. |
Yao Zhao; Mohammad Saleh; Peter J. Liu; | arxiv-cs.CL | 2020-06-17 |
1231 | CO-Search: COVID-19 Information Retrieval With Semantic Search, Question Answering, And Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here we present CO-Search, a retriever-ranker semantic search engine designed to handle complex queries over the COVID-19 literature, potentially aiding overburdened health workers in finding scientific answers during a time of crisis. |
ANDRE ESTEVA et. al. | arxiv-cs.IR | 2020-06-16 |
1232 | Understanding Points Of Correspondence Between Sentences For Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present an investigation into fusing sentences drawn from a document by introducing the notion of points of correspondence, which are cohesive devices that tie any two sentences together into a coherent text. We create a dataset containing the documents, source and fusion sentences, and human annotations of points of correspondence between sentences. |
LOGAN LEBANOFF et. al. | arxiv-cs.CL | 2020-06-09 |
1233 | Automatic Text Summarization Of COVID-19 Medical Research Articles Using BERT And GPT-2 IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our model provides abstractive and comprehensive information based on keywords extracted from the original articles. |
Virapat Kieuvongngam; Bowen Tan; Yiming Niu; | arxiv-cs.CL | 2020-06-02 |
1234 | Deep Learning Models For Automatic Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We will discuss in particular applications of pointer networks, hierarchical Transformers and Reinforcement Learning. |
Pirmin Lemberger; | arxiv-cs.CL | 2020-05-25 |
1235 | Rethinking and Improving Natural Language Generation with Layer-Wise Multi-View Decoding Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose layer-wise multi-view decoding, where for each decoder layer, together with the representations from the last encoder layer, which serve as a global view, those from other encoder layers are supplemented for a stereoscopic view of the source sequences. |
FENGLIN LIU et. al. | arxiv-cs.CL | 2020-05-16 |
1236 | Unsupervised Dual-Cascade Learning With Pseudo-Feedback Distillation For Query-Focused Extractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Dual-CES – a novel unsupervised, query-focused, multi-document extractive summarizer. |
Haggai Roitman; Guy Feigenblat; Doron Cohen; Odellia Boni; David Konopnicki; | www | 2020-05-13 |
1237 | Exploring Content Selection in Summarization of Novel Chapters IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a new summarization task, generating summaries of novel chapters using summary/chapter pairs from online study guides. |
Faisal Ladhak; Bryan Li; Yaser Al-Onaizan; Kathleen McKeown; | arxiv-cs.CL | 2020-05-04 |
1238 | Karcı Summarization: A Simple and Effective Approach for Automatic Text Summarization Using Karcı Entropy IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View |
Cengiz Hark; A. Karcı; | Inf. Process. Manag. | 2020-05-01 |
1239 | Discourse-Aware Unsupervised Summarization of Long Scientific Documents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose an unsupervised graph-based ranking model for extractive summarization of long scientific documents. |
Yue Dong; Andrei Mircea; Jackie C. K. Cheung; | arxiv-cs.CL | 2020-05-01 |
1240 | Attend To Medical Ontologies: Content Selection For Clinical Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we approach the content selection problem for clinical abstractive summarization by augmenting salient ontological terms into the summarizer. |
Sajad Sotudeh; Nazli Goharian; Ross W. Filice; | arxiv-cs.CL | 2020-04-30 |
1241 | Self-Supervised And Controlled Multi-Document Opinion Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a self-supervised setup that considers an individual document as a target summary for a set of similar documents. |
Hady Elsahar; Maximin Coavoux; Matthias Gallé; Jos Rozen; | arxiv-cs.CL | 2020-04-30 |
1242 | Text Segmentation By Cross Segment Attention IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose three transformer-based architectures and provide comprehensive comparisons with previously proposed approaches on three standard datasets. |
Michal Lukasik; Boris Dadachev; Gonçalo Simões; Kishore Papineni; | arxiv-cs.CL | 2020-04-29 |
1243 | Reference And Document Aware Semantic Evaluation Methods For Korean Language Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose evaluation metrics that reflect semantic meanings of a reference summary and the original document, Reference and Document Aware Semantic Score (RDASS). |
DONGYUB LEE et. al. | arxiv-cs.CL | 2020-04-29 |
1244 | Conditional Neural Generation Using Sub-Aspect Functions For Extractive News Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a neural framework that can flexibly control summary generation by introducing a set of sub-aspect functions (i.e. importance, diversity, position). |
Zhengyuan Liu; Ke Shi; Nancy F. Chen; | arxiv-cs.CL | 2020-04-29 |
1245 | Selective Attention Encoders By Syntactic Graph Convolutional Networks For Document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to use a graph to connect the parsing trees from the sentences in a document and utilize the stacked graph convolutional networks (GCNs) to learn the syntactic representation for a document. |
H. Xu; Y. Wang; K. Han; B. Ma; J. Chen and X. Li; | icassp | 2020-04-26 |
1246 | Experiments With LVT And FRE For Transformer Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we experiment with Large Vocabulary Trick and Feature-rich encoding applied to the Transformer model for Text Summarization. |
Ilshat Gibadullin; Aidar Valeev; | arxiv-cs.CL | 2020-04-26 |
1247 | Lite Transformer With Long-Short Range Attention IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present an efficient mobile NLP architecture, Lite Transformer to facilitate deploying mobile NLP applications on edge devices. |
Zhanghao Wu; Zhijian Liu; Ji Lin; Yujun Lin; Song Han; | arxiv-cs.CL | 2020-04-24 |
1248 | Exploring Explainable Selection To Control Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Therefore, to begin prying open the black box and to inject a level of control into the substance of the final summary, we developed a novel select-and-generate framework that focuses on explainability. |
Wang Haonan; Gao Yang; Bai Yu; Mirella Lapata; Huang Heyan; | arxiv-cs.CL | 2020-04-24 |
1249 | QURIOUS: Question Generation Pretraining For Text Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose question generation as a pretraining method, which better aligns with the text generation objectives. |
Shashi Narayan; Gonçalo Simoes; Ji Ma; Hannah Craighead; Ryan Mcdonald; | arxiv-cs.CL | 2020-04-23 |
1250 | Neural Abstractive Summarization With Structural Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a hierarchical encoder based on structural attention to model such inter-sentence and inter-document dependencies. |
Tanya Chowdhury; Sachin Kumar; Tanmoy Chakraborty; | arxiv-cs.CL | 2020-04-20 |
1251 | Extending Text Informativeness Measures To Passage Interestingness Evaluation (Language Model Vs. Word Embedding) Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we define the concept of Interestingness as a generalization of Informativeness, whereby the information need is diverse and formalized as an unknown set of implicit queries. |
Carlos-Emiliano González-Gallardo; Eric SanJuan; Juan-Manuel Torres-Moreno; | arxiv-cs.IR | 2020-04-14 |
1252 | PALM: Pre-training An Autoencoding&Autoregressive Language Model For Context-conditioned Generation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work presents PALM with a novel scheme that jointly pre-trains an autoencoding and autoregressive language model on a large unlabeled corpus, specifically designed for generating new text conditioned on context. |
BIN BI et. al. | arxiv-cs.CL | 2020-04-14 |
1253 | Probabilistic Model Of Narratives Over Topical Trends In Social Media: A Discrete Time Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address this issue, we propose a novel event-based narrative summary extraction framework. |
Toktam A. Oghaz; Ece C. Mutlu; Jasser Jasser; Niloofar Yousefi; Ivan Garibay; | arxiv-cs.SI | 2020-04-14 |
1254 | AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Building on the state-of-the-art encoding methods for summarization, we present two adaptive learning models: AREDSUM-SEQ that jointly considers salience and novelty during sentence selection; and a two-step AREDSUM-CTX that scores salience first, then learns to balance salience and redundancy, enabling the measurement of the impact of each aspect. |
Keping Bi; Rahul Jha; W. Bruce Croft; Asli Celikyilmaz; | arxiv-cs.CL | 2020-04-13 |
1255 | An In-depth Walkthrough On Evolution Of Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper aims to study the major trends in Neural Machine Translation, the state of the art models in the domain and a high level comparison between them. |
Rohan Jagtap; Dr. Sudhir N. Dhage; | arxiv-cs.CL | 2020-04-10 |
1256 | Query-Focused EHR Summarization To Aid Imaging Diagnosis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose and evaluate models that extract relevant text snippets from patient records to provide a rough case summary intended to aid physicians considering one or more diagnoses. |
DENIS JERED MCINERNEY et. al. | arxiv-cs.LG | 2020-04-09 |
1257 | Automated Utterance Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an utterance generation system which 1) uses extractive summarization to extract important sentences from the description, 2) uses multiple paraphrasing techniques to generate a diverse set of paraphrases of the title and summary sentences, and 3) selects good candidate paraphrases with the help of a novel candidate selection algorithm. |
Soham Parikh; Quaizar Vohra; Mitul Tiwari; | arxiv-cs.CL | 2020-04-07 |
1258 | Windowing Models For Abstractive Summarization Of Long Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose windowing models for neural abstractive summarization of (arbitrarily) long texts. |
Leon Schüller; Florian Wilhelm; Nico Kreiling; Goran Glavaš; | arxiv-cs.CL | 2020-04-07 |
1259 | Query-controllable Video Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce a method which takes a text-based query as input and generates a video summary corresponding to it. To foster the research of query-controllable video summarization and conduct our experiments, we introduce a dataset that contains frame-based relevance score labels. |
Jia-Hong Huang; Marcel Worring; | arxiv-cs.IR | 2020-04-07 |
1260 | At Which Level Should We Extract? An Empirical Analysis On Extractive Document Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show that unnecessity and redundancy issues exist when extracting full sentences, and extracting sub-sentential units is a promising alternative. |
Qingyu Zhou; Furu Wei; Ming Zhou; | arxiv-cs.CL | 2020-04-06 |
1261 | A News Image Captioning Approach Based on Multimodal Pointer‐generator Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: News image captioning aims to generate captions or descriptions for news images automatically, serving as draft captions for creating news image captions manually. News image … |
Jingqiang Chen; Hai Zhuge; | Concurrency and Computation: Practice and Experience | 2020-04-06 |
1262 | Amharic Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work we discuss one of these new novel approaches which combines curriculum learning with Deep Learning, this model is called Scheduled Sampling. |
Amr M. Zaki; Mahmoud I. Khalil; Hazem M. Abbas; | arxiv-cs.AI | 2020-03-30 |
1263 | Abstractive Summarization With Combination Of Pre-trained Sequence-to-Sequence And Saliency Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we investigated the effectiveness of combining saliency models that identify the important parts of the source text with the pre-trained seq-to-seq models through extensive experiments. |
Itsumi Saito; Kyosuke Nishida; Kosuke Nishida; Junji Tomita; | arxiv-cs.CL | 2020-03-29 |
1264 | Abstractive Text Summarization Based On Language Model Conditioning And Locality Modeling IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We explore to what extent knowledge about the pre-trained language model that is used is beneficial for the task of abstractive summarization. |
DMITRII AKSENOV et. al. | arxiv-cs.CL | 2020-03-29 |
1265 | Learning Syntactic And Dynamic Selective Encoding For Document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel neural architecture for document summarization. |
Haiyang Xu; Yahao He; Kun Han; Junwen Chen; Xiangang Li; | arxiv-cs.CL | 2020-03-24 |
1266 | Selective Attention Encoders By Syntactic Graph Convolutional Networks For Document Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to use a graph to connect the parsing trees from the sentences in a document and utilize the stacked graph convolutional networks (GCNs) to learn the syntactic representation for a document. |
HAIYANG XU et. al. | arxiv-cs.AI | 2020-03-17 |
1267 | StructSum: Summarization Via Structured Representations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a framework based on document-level structure induction for summarization to address these challenges. |
VIDHISHA BALACHANDRAN et. al. | arxiv-cs.CL | 2020-03-01 |
1268 | Clinical Text Summarization With Syntax-Based Negation And Semantic Concept Identification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our research objective is to use the biomedical ontology with semantic information, and take the advantage from the language hierarchical structure, the constituency tree, in order to identify the correct clinical concepts and the corresponding negation information, which is critical for summarizing clinical concepts from narrative text. |
Wei-Hung Weng; Yu-An Chung; Schrasing Tong; | arxiv-cs.CL | 2020-02-29 |
1269 | A More Abstractive Summarization Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We use normalized n-gram novelty scores as a metric for determining the level of abstraction. |
Satyaki Chakraborty; Xinya Li; Sayak Chakraborty; | arxiv-cs.CL | 2020-02-25 |
1270 | Discriminative Adversarial Search For Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a novel approach for sequence decoding, Discriminative Adversarial Search (DAS), which has the desirable properties of alleviating the effects of exposure bias without requiring external metrics. |
Thomas Scialom; Paul-Alexis Dray; Sylvain Lamprier; Benjamin Piwowarski; Jacopo Staiano; | arxiv-cs.CL | 2020-02-24 |
1271 | GRET: Global Representation Enhanced Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel global representation enhanced Transformer (GRET) to explicitly model global representation in the Transformer network. |
RONGXIANG WENG et. al. | arxiv-cs.CL | 2020-02-24 |
1272 | On The Impressive Performance Of Randomly Weighted Encoders In Summarization Tasks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the performance of untrained randomly initialized encoders in a general class of sequence to sequence models and compare their performance with that of fully-trained encoders on the task of abstractive summarization. |
Jonathan Pilault; Jaehong Park; Christopher Pal; | arxiv-cs.CL | 2020-02-20 |
1273 | Learning By Semantic Similarity Makes Abstractive Summarization Better IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we compare the generated summaries from recent LM, BART, and the reference summaries from a benchmark dataset, CNN/DM, using a crowd-sourced human evaluation metric. |
Wonjin Yoon; Yoon Sun Yeo; Minbyul Jeong; Bong-Jun Yi; Jaewoo Kang; | arxiv-cs.CL | 2020-02-18 |
1274 | Interpretable Multi-Headed Attention For Abstractive Summarization At Controllable Lengths IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose Multi-level Summarizer (MLS), a supervised method to construct abstractive summaries of a text document at controllable lengths. |
Ritesh Sarkhel; Moniba Keymanesh; Arnab Nandi; Srinivasan Parthasarathy; | arxiv-cs.CL | 2020-02-18 |
1275 | Two Huge Title And Keyword Generation Corpora Of Research Articles IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce two huge datasets for text summarization (OAGSX) and keyword generation (OAGKX) research, containing 34 million and 23 million records, respectively. |
Erion Çano; Ondřej Bojar; | arxiv-cs.CL | 2020-02-11 |
1276 | Attend To The Beginning: A Study On Using Bidirectional Attention For Extractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose attending to the beginning of a document, to improve the performance of extractive summarization models when applied to forum discussion data. |
Ahmed Magooda; Cezary Marcjan; | arxiv-cs.CL | 2020-02-09 |
1277 | Abstractive Summarization For Low Resource Data Using Domain Transfer And Data Synthesis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We proposed a template-based model to synthesize new data, which when incorporated into training further increased ROUGE scores. |
Ahmed Magooda; Diane Litman; | arxiv-cs.CL | 2020-02-09 |
1278 | CAWA: An Attention-Network for Credit Attribution Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present Credit Attribution With Attention (CAWA), a neural-network-based approach, that instead of using sentence-level labeled data, uses the set of class labels that are associated with an entire document as a source of distant-supervision. |
Saurav Manchanda; George Karypis; | aaai | 2020-02-07 |
1279 | Joint Parsing and Generation for Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we propose to remedy this problem by jointly generating a sentence and its syntactic dependency parse while performing abstraction. |
KAIQIANG SONG et. al. | aaai | 2020-02-07 |
1280 | Controlling The Amount of Verbatim Copying in Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a neural summarization model that, by learning from single human abstracts, can produce a broad spectrum of summaries ranging from purely extractive to highly generative ones. |
Kaiqiang Song; Bingqing Wang; Zhe Feng; Ren Liu; Fei Liu; | aaai | 2020-02-07 |
1281 | Aspect-Aware Multimodal Summarization for Chinese E-Commerce Products IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an abstractive summarization system that produces summary for Chinese e-commerce products. We construct a large-scale Chinese e-commerce product summarization dataset that contains approximately 1.4 million manually created product summaries that are paired with detailed product information, including an image, a title, and other textual descriptions for each product. |
HAORAN LI et. al. | aaai | 2020-02-07 |
1282 | Document Summarization with VHTM: Variational Hierarchical Topic-Aware Mechanism IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we propose a variational hierarchical model to holistically address both issues, dubbed VHTM. |
Xiyan Fu; Jun Wang; Jinghan Zhang; Jinmao Wei; Zhenglu Yang; | aaai | 2020-02-07 |
1283 | Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a principled approach to address the difficulties associated with RL-based solutions, namely, high-variance gradients, uninformative rewards and brittle training. |
LIQUN CHEN et. al. | aaai | 2020-02-07 |
1284 | MultiSumm: Towards A Unified Model for Multi-Lingual Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present MultiSumm, a novel multi-lingual model for abstractive summarization. As an additional contribution, we construct the first summarization dataset for Bosnian and Croatian, containing 177,406 and 204,748 samples, respectively. |
Yue Cao; Xiaojun Wan; Jinge Yao; Dian Yu; | aaai | 2020-02-07 |
1285 | Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To solve these problems, we tackle the tasks of answer selection and answer summary generation in CQA with a novel joint learning model. In addition, we construct a new large-scale CQA corpus, WikiHowQA, which contains long answers for answer selection as well as reference summaries for answer summarization. |
YANG DENG et. al. | aaai | 2020-02-07 |
1286 | Copy or Rewrite: Hybrid Summarization with Hierarchical Reinforcement Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address this problem, we propose HySum, a hybrid framework for summarization that can flexibly switch between copying sentence and rewriting sentence according to the degree of redundancy. |
Liqiang Xiao; Lu Wang; Hao He; Yaohui Jin; | aaai | 2020-02-07 |
1287 | SemSUM: Semantic Dependency Guided Neural Abstractive Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we incorporate semantic dependency graphs about predicate-argument structure of input sentences into neural abstractive summarization for the problem. |
Hanqi Jin; Tianming Wang; Xiaojun Wan; | aaai | 2020-02-07 |
1288 | Cross-Lingual Natural Language Generation Via Pre-Training IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work we focus on transferring supervision signals of natural language generation (NLG) tasks between multiple languages. |
ZEWEN CHI et. al. | aaai | 2020-02-07 |
1289 | Keywords-Guided Abstractive Sentence Summarization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose an abstractive sentence summarization method by applying guidance signals of keywords to both the encoder and the decoder in the sequence-to-sequence model. |
Haoran Li; Junnan Zhu; Jiajun Zhang; Chengqing Zong; Xiaodong He; | aaai | 2020-02-07 |
1290 | A Difference-of-Convex Programming Approach With Parallel Branch-and-Bound For Sentence Compression Via A Hybrid Extractive Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we design a hybrid extractive sentence compression model combining a probability language model and a parse tree language model for compressing sentences by guaranteeing the syntax correctness of the compression results. |
YI-SHUAI NIU et. al. | arxiv-cs.AI | 2020-02-02 |
1291 | Normalization Of Input-output Shared Embeddings In Text Generation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Based on linear algebra and statistical theories, this paper locates the shortcoming of existed input-output embedding weight sharing method, then raises methods for improving input-output weight shared embedding, among which methods of normalization of embedding weight matrices show best performance. |
Jinyang Liu; Yujia Zhai; Zizhong Chen; | arxiv-cs.CL | 2020-01-22 |
1292 | Audio Summarization With Audio Features And Probability Distribution Divergence Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we focus on audio summarization based on audio features and the probability of distribution divergence. |
Carlos-Emiliano González-Gallardo; Romain Deveaud; Eric SanJuan; Juan-Manuel Torres-Moreno; | arxiv-cs.CL | 2020-01-20 |
1293 | Length-controllable Abstractive Summarization By Guiding With Summary Prototype IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new length-controllable abstractive summarization model. |
ITSUMI SAITO et. al. | arxiv-cs.CL | 2020-01-20 |
1294 | Show, Recall, and Tell: Image Captioning with Recall Mechanism IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we pro-pose a novel recall mechanism to imitate the way human con-duct captioning. |
Li Wang; Zechen Bai; Yonghua Zhang; Hongtao Lu; | arxiv-cs.CV | 2020-01-15 |
1295 | A Methodology for Open Information Extraction and Representation from Large Scientific Corpora: The CORD-19 Data Exploration Use Case IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The usefulness of automated information extraction tools in generating structured knowledge from unstructured and semi-structured machine-readable documents is limited by … |
Dimitris Papadopoulos; Nikolaos Papadakis; Antonis Litke; | Applied Sciences | 2020-01-01 |
1296 | A Survey of Distinctive Prominence of Automatic Text Summarization Techniques Using Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View |
Apurva D. Dhawale; Sonali B. Kulkarni; Vaishali Kumbhakarna; | 2020-01-01 | |
1297 | A Discussion on Various Methods in Automatic Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Madhuri P. Karnik; D. V. Kodavade; | 2020-01-01 | |
1298 | CLTS: A New Chinese Long Text Summarization Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We present CLTS, a Chinese long text summarization dataset, in order to solve the problem that large-scale and high-quality datasets are scarce in automatic summarization, which … |
Xiaojun Liu; Chuang Zhang; Xiaojun Chen; Yanan Cao; Jinpeng Li; | 2020-01-01 | |
1299 | Fine-Tuning Textrank for Legal Document Summarization: A Bayesian Optimization Based Approach IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization techniques have a very high applicability in the legal domain, due to the complex and lengthy nature of legal documents. Most of the classical text … |
Deepali Jain; Malaya Dutta Borah; Anupam Biswas; | Forum for Information Retrieval Evaluation | 2020-01-01 |
1300 | A Semantically Rich Framework for Knowledge Representation of Code of Federal Regulations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Federal government agencies and organizations doing business with them have to adhere to the Code of Federal Regulations (CFR). The CFRs are currently available as large text … |
Karuna Pande Joshi; Srishty Saha; | Digital Government: Research and Practice | 2020-01-01 |
1301 | Leveraging Pre-Trained Language Model for Summary Generation on Short Text Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Bidirectional Encoder Representations from Transformers represents the latest incarnation of pre-trained language models which have been obtained a satisfactory effect in text … |
Shuai Zhao; Fucheng You; Zeng Yuan Liu; | IEEE Access | 2020-01-01 |
1302 | Comparative Study of Sentiment Analysis and Text Summarization for Commercial Social Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid shift towards digitalization today has actually transferred the market to an entirely digitalized platform. The participation of such a large number of users has given … |
Hamza Abubakar Kheruwala; Jimeet Viren Shah; Jai Prakash Verma; | 2020-01-01 | |
1303 | Unsupervised Automatic Text Summarization of Konkani Texts Using K-means with Elbow Method Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text Summarization is an emerging field of research in Natural Language Processing (NLP). A bulk of the work is related to texts in English and other popular languages. This paper … |
Jovi D’Silva; Uzzal Sharma; | International journal of engineering research and technology | 2020-01-01 |
1304 | Chinese Long Text Summarization Using Improved Sequence-to-sequence Lstm Related Papers Related Patents Related Grants Related Venues Related Experts View |
Zanjie Yao; Aixiang Chen; Han Xie; | 2020-01-01 | |
1305 | Improving NER Performance By Applying Text Summarization on Pharmaceutical Articles Related Papers Related Patents Related Grants Related Venues Related Experts View |
Jovana Dobreva; Nasi Jofche; Milos Jovanovik; Dimitar Trajanov; | 2020-01-01 | |
1306 | Causal Maps for Multi-Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Concept maps are concise graphical representations of text data which have been shown to be applicable as a tool for text summarization and downstream tasks. Most prior work has … |
Sasha Strelnikoff; Aruna Jammalamadaka; Dana Warmsley; | 2020 IEEE International Conference on Big Data (Big Data) | 2020-01-01 |
1307 | Identifying of Decision Components In Thai Civil Case Decision By Text Classification Technique Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A Thai civil case decision document is typically presented in a semi-structured form. Generally, Thai civil case decision documents consist of four major components comprising the … |
Jantima Polpinij; Poramin Bheganan; Bancha Luaphol; Chumsak Sibunruang; Khanista Namee; | 2020-01-01 | |
1308 | EdgeSumm: Graph-based Framework for Automatic Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Searching the Internet for a certain topic can become a daunting task because users cannot read and comprehend all the resulting texts. Automatic Text summarization (ATS) in this … |
Wafaa S. El-Kassas; Cherif R. Salama; Ahmed A. Rafea; Hoda K. Mohamed; | Inf. Process. Manag. | 2020-01-01 |
1309 | Text Summarization Using QA Corpus for User Interaction Model QA System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Document summarization is capable of generating user query relevant, precise summaries from the original document for user needs. To reduce the response time summary generation, … |
K. Karpagam; A. Saradha; K. Manikandan; K. Madusudanan; | International Journal of Education and Management … | 2020-01-01 |
1310 | Motivations, Methods and Metrics of Misinformation Detection: An NLP Perspective IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: ive summarization is also a relevant task that can be useful for facilitating misinformation detection. Specifically, the summarization model can be applied to identify the … |
Qi Su; Mingyu Wan; Xiaoqian Liu; Chu-Ren Huang; | Natural Language Processing Research | 2020-01-01 |
1311 | Natural Language Processing Based Abstractive Text Summarization of Reviews Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Humans are habituated to remember only relevant points of an article. The way synopsis of a book is used to understand the gist of it and decide whether it is interesting, … |
Janice Shah; Manasvi Sagathiya; Kareena Redij; Varsha Hole; | 2020 International Conference on Electronics and … | 2020-01-01 |
1312 | Text Summarization Challenge: An Evaluation Program for Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In Japan, the Text Summarization Challenge (TSC), the first text summarization evaluation of its kind, was conducted in 2000–2001 as a part of the NTCIR (NII-NACSIS Test … |
Hidetsugu Nanba; Tsutomu Hirao; Takahiro Fukushima; Manabu Okumura; | 2020-01-01 | |
1313 | Annobot: Platform for Annotating and Creating Datasets Through Conversation with A Chatbot Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: In this paper, we introduce Annobot: a platform for annotating and creating datasets through conversation with a chatbot. This natural form of interaction has allowed us to create … |
Rafał Poświata; Michał Perełkiewicz; | 2020-01-01 | |
1314 | Selective and Coverage Multi-head Attention for Abstractive Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xuwen Zhang; Gongshen Liu; | 2020-01-01 | |
1315 | Design of Optimal Search Engine Using Text Summarization Through Artificial Intelligence Techniques IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The … |
Kaushik Sekaran; P. Chandana; J. Rethna Virgil Jeny; Maytham N. Meqdad; Seifedine Kadry; | TELKOMNIKA (Telecommunication Computing Electronics and … | 2020-01-01 |
1316 | Subject Review: Text Clustering Algorithms Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Clustering algorithms are taking attention in recent times, according to a huge amount of datasets and the growth of parallelized computing architectures. The goal of … |
Zuhair Hussein Ali; Amal Abbas Kadhim; Azal Minshed Abid; | 2020-01-01 | |
1317 | A Novel Approach in Automated Bengali Text Summarizing By Statistical and Sentence Similarity Method Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: World is now moving in faster speed with the blessings of technology. Information is vastly stored in the cloud instead of hard copy documents or compact disk. Hence, to keep … |
Md. Sadek Hossain Asif; | 2020-01-01 | |
1318 | Extractive Multi-Document Summarization Model Based On Different Integrations of Double Similarity Measures Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology … |
Dheyaa Abdulameer Mohammed; Nasreen J. Kadhim; | Iraqi journal of science | 2020-01-01 |
1319 | News Text Summarization Based on Multi-Feature and Fuzzy Logic IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the last 70 years, the automatic text summarization work has become more and more important because the amount of data on the Internet is increasing so fast, and automatic text … |
Yan Du; Hua Huo; | IEEE Access | 2020-01-01 |
1320 | A Brief Note on DocumentSummarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Document Summarization is a very challenging task in text mining. Summarizing a large document in concise short sentences which is a subgroup of the initial text is called as … |
Abhya Tripathi; | 2020-01-01 | |
1321 | UDHR – Unified Decentralized Health Repository Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The healthcare domain is always upgrading itself in order to provide better care. The use of digital media for medical purposes has been on the rise. Naturally, these methods are … |
PREMANAND P. GHADEKAR et. al. | 2020-01-01 | |
1322 | MAMHOA: A Multi-agent Meta-heuristic Optimization Algorithm with An Approach for Document Summarization Issues Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Today, given the increasing volume of information and the difficulty of using them for specific applications such as email, websites, news, etc., the use of automated information … |
Seyed Hossein Mirshojaee; Behrooz Masoumi; Esmaeil Zeinali; | Journal of Ambient Intelligence and Humanized Computing | 2020-01-01 |
1323 | A Joint Sentence Scoring and Selection Framework for Neural Extractive Document Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extractive document summarization methods aim to extract important sentences to form a summary. Previous works perform this task by first scoring all sentences in the document … |
QINGYU ZHOU et. al. | IEEE/ACM Transactions on Audio, Speech, and Language … | 2020-01-01 |
1324 | Deep Learning Based Abstractive Text Summarization: Approaches, Datasets, Evaluation Measures, and Challenges Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, the volume of textual data has rapidly increased, which has generated a valuable resource for extracting and analysing information. To retrieve useful knowledge … |
Dima Suleiman; Arafat Awajan; | Mathematical Problems in Engineering | 2020-01-01 |
1325 | Extraction and Portrait of Knowledge Points for Open Learning Resources Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This article explores how to use the technology of text summarization and keyword extraction to automatically extract key knowledge points from massive educational resources and … |
JIAN YU et. al. | 2020-01-01 | |
1326 | Text Summarization Menggunakan Library Natural Language Toolkit (NLTK) Berbasis Pemrograman Python Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Tujuan dari penulisan jurnal ini untuk memudahkan pembaca dalam meringkas berita khususnya berita bola dengan menggunakan library NLTK pada pemrograman Python. NLTK, adalah paket … |
EDOARDO JOFAN RIFANO et. al. | 2020-01-01 | |
1327 | Machine Learning Based Text Summarization for Turkish News Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we propose an automatic text summarization model for Turkish news articles using machine learning models. Our proposed model uses sentence position, speech … |
Yavuz Selim Kartal; Mücahid Kutlu; | 2020 28th Signal Processing and Communications Applications … | 2020-01-01 |
1328 | Graph-Based Multi-document Text Summarization Using NLP Related Papers Related Patents Related Grants Related Venues Related Experts View |
Abhilasha More; Vipul Dalal; | 2020-01-01 | |
1329 | Multi-document Text Summarization Tool Related Papers Related Patents Related Grants Related Venues Related Experts View |
Richeeka Bathija; Pranav Agarwal; Rakshith Somanna; G. B. Pallavi; | 2020-01-01 | |
1330 | Survey of Scientific Document Summarization Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The number of scientic or research papers published every year is growing at an exponential rate, which has led to an intensive research in scientic document summarization. The … |
K SheenaKurian; Sheena Mathew; | Comput. Sci. | 2020-01-01 |
1331 | A Novel Sentence Scoring Method for Extractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Kamal Sarkar; Sohini Roy Chowdhury; | 2020-01-01 | |
1332 | Text Summarization Using Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View |
Kota Prudhvi; A. Bharath Chowdary; P. Subba Rami Reddy; P. Lakshmi Prasanna; | 2020-01-01 | |
1333 | LegalOps: A Summarization Corpus of Legal Opinions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We present a new, large-scale corpus for training and evaluating text summarization systems on legal opinions, called LegalOps. The corpus includes ~14K opinions together with … |
Andrew Gargett; Rob Firth; Nikolaos Aletras; | 2020 IEEE International Conference on Big Data (Big Data) | 2020-01-01 |
1334 | Automatic Text Summarization from Unstructured Text Using Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mamta Aswani; | 2020-01-01 | |
1335 | On The Use of Positive Definite Symmetric Kernels for Summary Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The task of creating a short, accurate and fluent summary starting from a larger text document or group of documents is called text summarization. When the summary is generated by … |
Claudiu Popescu; Lacrimioara Grama; Corneliu Rusu; | 2020 13th International Conference on Communications (COMM) | 2020-01-01 |
1336 | A*-Reduct: A Heuristic Rough Set Based Feature Selection Algorithm and Its Application to Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the emergence Big data scenario selection of features has assumed a very important role in today’s data processing world. Handling a large volume of data, irrespective of the … |
Nidhika Yadav; Niladri Chatterjee; | 2020-01-01 | |
1337 | A Dataset for Exploring Gaze Behaviors in Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization has been a hot research topic for years. Though most of the existing studies only use the content itself to generate the summaries, researchers … |
Kun Yi; Yu Guo; Weifeng Jiang; Zhi Wang; Lifeng Sun; | Proceedings of the 11th ACM Multimedia Systems Conference | 2020-01-01 |
1338 | Automatic Summary Extraction in Texts Using Genetic Algorithms Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is one of the applications of natural language processing that has been studied for a long time. The increase in the amount of information in web … |
Abdullah Ammar Karcioglu; Ahmet Cahit Yasa; | 2020 28th Signal Processing and Communications Applications … | 2020-01-01 |
1339 | A Comparative Analysis and Critical Review of Summarization Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Unstructured data is outcome of various major business applications. Summarizing unstructured data is considered as a significant task in this era of smart digital evolution. Text … |
MAUSUMI GOSWAMI et. al. | Journal of Computational and Theoretical Nanoscience | 2020-01-01 |
1340 | CFCSS : Based on CF Network Convolutional Seq2Seq Model for Abstractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Aiming to provide automatic document summarization model with channel dependency and global information to capture deeply text architecture and semantic content, this paper puts … |
Qingmin Liang; Ling Lu; Tianji Chang; Wu Yang; | 2020 15th IEEE Conference on Industrial Electronics and … | 2020-01-01 |
1341 | Unstructured Text Documents Summarization With Multi-Stage Clustering IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In natural language processing, text summarization is an important application used to extract desired information by reducing large text. Existing studies use keyword-based … |
Muhammad Yahya Saeed; Muhammad Awais; Ramzan Talib; Muhammad Younas; | IEEE Access | 2020-01-01 |
1342 | Natural Language Processing Based Text Summarization and Querying Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Learning skills play a very important role to build a student’s foundation for a language. It becomes difficult for students to analyze the important information available in an … |
Umang Mavani; Devashri Shinde; Aditi Pednekar; Safa Hamdare; | 2020 Fourth International Conference on Inventive Systems … | 2020-01-01 |
1343 | Arabic Text Summarization Using Deep Learning Approach IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Natural language processing has witnessed remarkable progress with the advent of deep learning techniques. Text summarization, along other tasks like text translation and … |
Molham Al-Maleh; Said Desouki; | Journal of Big Data | 2020-01-01 |
1344 | Towards Hybrid Model for Automatic Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The overflowing of textual data on the web needs an efficient tool that is able to manage and process data. In this context, automatic text summarization has shown a great … |
Ji Pei; Rim Hantach; Sarra Ben Abbès; Philippe Calvez; | 2020 19th IEEE International Conference on Machine Learning … | 2020-01-01 |
1345 | Implementasi Algoritma Graf Dan Algoritma Genetika Pada Peringkasan Single Document Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In today’s technological advancements, finding information is easier and faster. But not a little information that is not true or commonly referred to as hoaxes. Therefore, … |
Lina Dwi Yulianti; Setio Basuki; Yufis Azhar; | 2020-01-01 | |
1346 | Model Peringkasan Teks Ekstraktif Dwibahasa Menggunakan Fitur Kekangan Corak Tekstual (Bilingual Extractive Text Summarization Model Using Textual Pattern Constraints) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Di dalam era pencarian maklumat digital, sebuah ringkasan yang dijana secara automatik dapat membantu pembaca mendapatkan maklumat penting dan relevan dengan lebih mudah. … |
Suraya Alias; Mohd Shamrie Sainin; Siti Khaotijah Mohammad; | GEMA Online Journal of Language Studies | 2020-01-01 |
1347 | Accountability of NLP Tools in Text Summarization for Indian Languages IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: 258 DOI: http://dx.doi.org/10.37398/JSR.2020.640149 Abstract: In the era of digital world, online information is growing exponentially. It leads to emergence of inconvenient … |
Pradeepika Verma; Anshul Verma; | Journal of Scientific Research | 2020-01-01 |
1348 | A Review on Text Summarization Techniques IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, an enormous amount of text data from diversified sources has been emerged day-by-day. This huge amount of data carries essential information and knowledge that … |
Pradeepika Verma; Anshul Verma; | Journal of Scientific Research | 2020-01-01 |
1349 | Fuzzy Logic Based Hybrid Model for Automatic Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the contemporary age of information, accessing data becomes easy, but finding knowledge is very difficult. The participation & publishing of information has consequently … |
Akshi Kumar; Aditi Sharma; Anand Nayyar; | Proceedings of the 2020 5th International Conference on … | 2020-01-01 |
1350 | News Editorials: Towards Summarizing Long Argumentative Texts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The automatic summarization of argumentative texts has hardly been explored. This paper takes a further step in this direction, targeting news editorials, i.e., opinionated … |
SHAHBAZ SYED et. al. | 2020-01-01 | |
1351 | HOLMS: Alternative Summary Evaluation with Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Efficient document summarization requires evaluation measures that can not only rank a set of systems based on an average score, but also highlight which individual summary is … |
Yassine Mrabet; Dina Demner-Fushman; | 2020-01-01 | |
1352 | Controllable Abstractive Sentence Summarization with Guiding Entities Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Entities are the major proportion and build up the topic of text summaries. Although existing text summarization models can produce promising results of automatic metrics, for … |
Changmeng Zheng; Yi Cai; Guanjie Zhang; Qing Li; | 2020-01-01 | |
1353 | An Unsupervised Constrained Optimization Approach to Compressive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic summarization is typically aimed at selecting as much information as possible from text documents using a predefined number of words. Extracting complete sentences into … |
Natalia Vanetik; Marina Litvak; Elena Churkin; Mark Last; | Inf. Sci. | 2020-01-01 |
1354 | Advancement of Text Summarization Using Machine Learning and Deep Learning: A Review Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid growth in the text available on the Internet in the variety of forms demands in-depth research for summarizing text automatically. The summarized form produced from one … |
Rishi Kotadiya; Shivangi Bhatt; Uttam Chauhan; | 2020-01-01 | |
1355 | A SIMPLE AND EFFICIENT TEXT SUMMARIZATION MODEL FOR ODIA TEXT DOCUMENTS Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sagarika Pattnaik; Ajit Kumar Nayak; | Indian Journal of Computer Science and Engineering | 2020-01-01 |
1356 | Topic Level Summary Generation Using BERT Induced Abstractive Summarization Model IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, the implemented system channels an idea called Topic level summary. The topic level summary is a collective summary in text format which consists of relevant … |
Mayank Ramina; Nihar Darnay; Chirag Ludbe; Ajay Dhruv; | 2020 4th International Conference on Intelligent Computing … | 2020-01-01 |
1357 | Enhance Content Selection for Multi-Document Summarization with Entailment Relation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is one of the common tasks in natural language processing. The main task is to generate a shorter version based on the original text and maintain … |
Yu-Yun Wang; Jhen-Yi Wu; Tzu-Hsuan Chou; Ying-Jia Lin; Hung-Yu Kao; | 2020 International Conference on Technologies and … | 2020-01-01 |
1358 | Plausibility-promoting Generative Adversarial Network for Abstractive Text Summarization with Multi-task Constraint IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive text summarization is an essential task in natural language processing, which aims to generate concise and condensed summaries retaining the salient information of the … |
MIN YANG et. al. | Inf. Sci. | 2020-01-01 |
1359 | Interactive Self-Attentive Siamese Network for Biomedical Sentence Similarity IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The determination of semantic similarity between sentences is an important component in natural language processing (NLP) tasks such as text retrieval and text summarization. Many … |
ZHENGGUANG LI et. al. | IEEE Access | 2020-01-01 |
1360 | Abstractive Text Summarization on Google Search Results Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Internet has become the forefront of our lives, technological advancements help people in an efficient and better way. The capitalists, educators, analysts all share a lot of … |
Dikshita Patel; Nisarg Shah; Vrushali Shah; Varsha Hole; | 2020 4th International Conference on Intelligent Computing … | 2020-01-01 |
1361 | A Multi-task Learning Approach to Text Simplification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose a multi-task learning approach to reducing text complexity which combines text summarization and simplification methods. For the purposes of this research, two datasets … |
Anna Dmitrieva; Jörg Tiedemann; | Recent Trends in Analysis of Images, Social Networks and … | 2020-01-01 |
1362 | Knowledge Distillation on Extractive Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large-scale pre-trained frameworks have shown state-of-the-art performance in several natural language processing tasks. However, the costly training and inference time are great … |
Ying-Jia Lin; Daniel Tan; Tzu-Hsuan Chou; Hung-Yu Kao; Hsin-Yang Wang; | 2020 IEEE Third International Conference on Artificial … | 2020-01-01 |
1363 | Text Summarization Generation Based on Semantic Similarity Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, with the continuous development of deep learning and natural language processing, sequence-to-sequence based model has become the mainstream of abstractive … |
Jingjing Chen; Fucheng You; | 2020 International Conference on Intelligent … | 2020-01-01 |
1364 | Hybrid Algorithm to Generate Summary of Documents By Extracting Keywords Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In modern times, data is growing rapidly in every domain such as news, social media, banking, education, etc. Due to the excessiveness of data, there is a need of automatic … |
Devanshi Parikh; Surbhi Patel; Dr. Hiren Joshi; | International Journal of Engineering Research and | 2020-01-01 |
1365 | ISSE: A New Iterative Sentence Scoring and Extraction Scheme for Automatic Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: An ever-increasing volume of contextual data appearing on various types of media overwhelms users sharing information, as well as bringing up storage concerns. Automatic text … |
Saeed Hosseinabadi; Manoochehr Kelarestaghi; Farshad Eshghi; | International Journal of Computers and Applications | 2020-01-01 |
1366 | CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Our system participates in two shared tasks, CL-SciSumm 2020 and LongSumm 2020. In the CL-SciSumm shared task, based on our previous work, we apply more machine learning methods … |
LEI LI et. al. | 2020-01-01 | |
1367 | Abstractive Sentence Summarization with Encoder-Convolutional Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summarization is the task of condensing a piece of text to produce a short version while preserving important elements and the meaning of content There have two main methods to … |
Toi Nguyen; Toai Le; Nhi-Thao Tran; | 2020 12th International Conference on Knowledge and Systems … | 2020-01-01 |
1368 | Monash-Summ@LongSumm 20 SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Scholarly Document Processing (SDP) workshop is to encourage more efforts on natural language understanding of scientific task. It contains three shared tasks and we … |
Jiaxin Ju; Ming Liu; Longxiang Gao; Shirui Pan; | 2020-01-01 | |
1369 | Using Pre-Trained Transformer for Better Lay Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we tack lay summarization tasks, which aim to automatically produce lay summaries for scientific papers, to participate in the first CL-LaySumm 2020 in SDP workshop … |
Seungwon Kim; | 2020-01-01 | |
1370 | LegoNet – Classification and Extractive Summarization of Indian Legal Judgments with Capsule Networks and Sentence Embeddings Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we propose the LegoNet – a system to classify and summarize legal judgments using Sentence Embedding, Capsule Networks and Unsupervised Extractive Summarization. … |
Harshith R. Acharya; Aditya D. Bhat; K. Avinash; Ramamoorthy Srinath; | J. Intell. Fuzzy Syst. | 2020-01-01 |
1371 | Evolutionary Automatic Text Summarization Using Cluster Validation Indexes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The main problem for generating an extractive automatic text summary (EATS) is to detect the key themes of a text. For this task, unsupervised approaches cluster the sentences of … |
Néstor Hernández Castañeda; René Arnulfo García-Hernández; Yulia Ledeneva; Ángel Hernández-Castañeda; | Computación y Sistemas | 2020-01-01 |
1372 | Mining Scientific and Technical Literature Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this chapter, the authors study text mining technologies such as knowledge extraction and summarization on scientific and technical literature. First, they analyze the needs of … |
Junsheng Zhang; Wen Zeng; | 2020-01-01 | |
1373 | Data Text Mining Based on Swarm Intelligence Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the great growth of data on the web, mining to extract the most informative data as a conceptual brief would be beneficial for certain users. Therefore, there is great … |
Mohamed Atef Mosa; | 2020-01-01 | |
1374 | The Development of Single-Document Abstractive Text Summarizer During The Last Decade Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As the number of electronic text documents is increasing so is the need for an automatic text summarizer. The summary can be extractive, compression, or abstractive. In the … |
Amal M. Al-Numai; Aqil M. Azmi; | 2020-01-01 | |
1375 | Combining Machine Learning and Natural Language Processing for Language-Specific, Multi-Lingual, and Cross-Lingual Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The recent advances in multimedia and web-based applications have eased the accessibility to large collections of textual documents. To automate the process of document analysis, … |
Luca Cagliero; Paolo Garza; Moreno La Quatra; | 2020-01-01 | |
1376 | Personalized Text Summarization Based on Gaze Patterns Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the explosive growth of online content, summarization has become important for users to grasp information quickly. However, existing summarization only provides static and … |
Kun Yi; Yu Guo; Zhi Wang; Lifeng Sun; Wenwu Zhu; | 2020 IEEE Conference on Multimedia Information Processing … | 2020-01-01 |
1377 | Divide and Conquer: From Complexity to Simplicity for Lay Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: We describe our approach for the 1st Computational Linguistics Lay Summary Shared Task CL-LaySumm20. The task is to produce non-technical summaries of scholarly documents. The … |
ROCHANA CHATURVEDI et. al. | 2020-01-01 | |
1378 | Improved Approach to Extract Knowledge from Unstructured Data Using Applied Natural Language Processing Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Extraction of meaningful knowledge from a unstructured data is a complex task. In the literature, efforts have been made using text mining approaches. These approaches employ rich … |
U. Mahender; M. Kumara Swamy; Hafeezuddin Shaik; Sheo Kumar; | 2020-01-01 | |
1379 | Automatic Text Summarization for Code- Mixed Language Using Fuzzy Logic Related Papers Related Patents Related Grants Related Venues Related Experts View |
Madhuri A. Tayal; | Biochemical and Biophysical Research Communications | 2020-01-01 |
1380 | A Topic Information Fusion and Semantic Relevance for Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the continuous development of deep learning, pre-trained models have achieved sound effects in the field of natural language processing. However, text summarization research … |
Fucheng You; Shuai Zhao; Jingjing Chen; | IEEE Access | 2020-01-01 |
1381 | Text Summarization and Classification of Clinical Discharge Summaries Using Deep Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper implements the automated classification of patient discharge notes into standard disease labels which includes the name of the diagnostic procedure required. In this … |
ALIZAR MARCHAWALA et. al. | 2020-01-01 | |
1382 | A Text Summarization Method Based on Semantic Similarity Among Sentences Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, more and more attention has been paid to the graph-based text summarization. In terms of this method, the document is transformed into a text graph and then … |
Yu-bing Hou; | DEStech Transactions on Social Science, Education and Human … | 2020-01-01 |
1383 | Textual Analysis of End User License Agreement for Red-flagging Potentially Malicious Software Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: New software and updates are downloaded by end users every day. Each dowloaded software has associated with it an End Users License Agreements (EULA), but this is rarely read. An … |
Behraj Khan; Tahir Syed; Zeshan Khan; Muhammad Rafi; | 2020 International Conference on Electrical, Communication, … | 2020-01-01 |
1384 | From Web to SMS: A Text Summarization of Wikipedia Pages with Character Limitation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Wikipedia is one of the main sources of information on the Web. But the access to this content may be difficult especially when using a basic telephone without browsing capability … |
Jean Louis Fendji Kedieng Ebongue; B. A. H. Aminatou; | EAI Endorsed Trans. Creative Technol. | 2020-01-01 |
1385 | Automatic Text Summarization Model Using Seq2Seq Technique Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Increasing acquisition of digitization over the information storing and processing in our daily lives has increased the demand of digitization in multiple facets including in … |
Chandrika Prasad; Jagdish S. Kallimani; Divakar Harekal; Nicy Sharma; | 2020 Fourth International Conference on I-SMAC (IoT in … | 2020-01-01 |
1386 | Abstractive Meeting Summarization By Hierarchical Adaptive Segmental Network Learning with Multiple Revising Steps IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive meeting summarization is a challenging problem in natural language understanding, which automatically generates the condensed summary covering the important points in … |
JIYUAN ZHENG et. al. | Neurocomputing | 2020-01-01 |
1387 | Legal Case Summarization: An Application for Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Today in the realm of developing advances, there is a gigantic development in technologies. These days every single theme identified with research is accessible on the web. … |
Kanika Agrawal; | 2020 International Conference on Computer Communication and … | 2020-01-01 |
1388 | Extractive Summarization of Telugu Documents Using TextRank Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Reading large and lengthy documents is a tedious and time-consuming task. A summary of the same document gives us an overall idea of what the document is all about. Automated … |
K Usha Manjari; | 2020 Fourth International Conference on I-SMAC (IoT in … | 2020-01-01 |
1389 | Automatic Text Summarization for Files Using TF-IDF Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts View |
Sukesha Sarwade; Sneha Lakhanwar Lakhanwar; Sanskruti More; Ashwini Sonawane; Manjushree Mahajan; | International journal of scientific research in science, … | 2020-01-01 |
1390 | An Experiment on Text Summarization: Frequent Terms and Concept Definition Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper explores the idea that the main concepts of definitions are very good candidates for the process of automatic summarization. Our objective is to develop a methodology … |
Cristian Niculita; Luminita Dumitriu; | 2020 24th International Conference on System Theory, … | 2020-01-01 |
1391 | Review of Automatic Text Summarization Techniques & Methods IF:4 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization automatically produces a summary containing important sentences and includes all relevant important information from the original document. One of the main … |
ADHIKA PRAMITA WIDYASSARI et. al. | Journal of King Saud University – Computer and Information … | 2020-01-01 |
1392 | Two-Level Text Summarization with Natural Language Processing Related Papers Related Patents Related Grants Related Venues Related Experts View |
Rupali Hande; Avinash Sidhwani; Deepesh Sidhwani; Monil Shiv; Divesh Kewalramani; | 2020-01-01 | |
1393 | Extractive Automatic Text Summarization Based on Lexical-Semantic Keywords IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The automatic text summarization (ATS) task consists in automatically synthesizing a document to provide a condensed version of it. Creating a summary requires not only selecting … |
Ángel Hernández-Castañeda; René Arnulfo García-Hernández; Yulia Ledeneva; Christian Eduardo Millán-Hernández; | IEEE Access | 2020-01-01 |
1394 | A Hybrid Long Arabic Text Summarization System Based on Integrated Approach Between Abstractive and Extractive Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Inevitably generating a robust summary from a long Arabic document is a challenging task owing to the fact that Arabic is a complex language and has unique attributes. In this … |
Abdullah Fadel; G. Bora Esmer; | Proceedings of the 2020 6th International Conference on … | 2020-01-01 |
1395 | The Impact of Key Ideas on Automatic Deception Detection in Text Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, with the rise of the Internet, the automatic deception detection in text is an important task to recognize those of documents that try to make people believe in … |
Ángel Hernández-Castañeda; René Arnulfo García-Hernández; Yulia Ledeneva; Christian Eduardo Millán-Hernández; | Computación y Sistemas | 2020-01-01 |
1396 | Ground Truth Spanish Automatic Extractive Text Summarization Bounds Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The textual information has accelerated growth in the most spoken languages by native Internet users, such as Chinese, Spanish, English, Arabic, Hindi, Portuguese, Bengali, … |
Griselda Areli Matias Mendoza; Yulia Ledeneva; René Arnulfo García-Hernández; Mikhail Alexandrov; Ángel Hernández-Castañeda; | Computación y Sistemas | 2020-01-01 |
1397 | Global Encoding for Long Chinese Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is one of the significant tasks of natural language processing, which automatically converts text into a summary. Some summarization systems, for short/long … |
Xue-Feng Xi; Zhou Pi; Guodong Zhou; | ACM Transactions on Asian and Low-Resource Language … | 2020-01-01 |
1398 | Study on Abstractive Text Summarization Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As there is an increase in the usage of digital applications, the availability of data generated has increased to a tremendous scale. Data is an important component in almost … |
Parth Rajesh Dedhia; Hardik Pradeep Pachgade; Aditya Pradip Malani; Nataasha Raul; Meghana Naik; | 2020 International Conference on Emerging Trends in … | 2020-01-01 |
1399 | Team Up! Cohesive Text Summarization Scoring Sentence Coalitions Related Papers Related Patents Related Grants Related Venues Related Experts View |
Inez Okulska; | 2020-01-01 | |
1400 | Extractive Single Document Summarization Using NSGA-II Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is the process of automatically retrieving the most relevant information from a large amount of textual data and representing the retrieved information in a … |
A. R. Manju Priya; Deepa Gupta; | 2020-01-01 | |
1401 | The Use of Semantic Role Labelling with Triangle-Graph Based Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Yazan Alaya AL-Khassawneh; | 2020-01-01 | |
1402 | TWEETSUM: Event Oriented Social Summarization Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With social media becoming popular, a vast of short and noisy messages are produced by millions of users when a hot event happens. Developing social summarization systems becomes … |
Ruifang He; Liangliang Zhao; Huanyu Liu; | 2020-01-01 | |
1403 | SumTitles: A Summarization Dataset with Low Extractiveness Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The existing dialogue summarization corpora are significantly extractive. We introduce a methodology for dataset extractiveness evaluation and present a new low-extractive corpus … |
Valentin Malykh; Konstantin Chernis; Ekaterina Artemova; Irina Piontkovskaya; | 2020-01-01 | |
1404 | An Adaptation of A F-measure for Automatic Text Summarization By Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we propose to adapt the F-measure to evaluate an automatic summaries of texts; we the main key to our proposal is to prove that the automatic summary task can be … |
Mohamed Amine Boudia; Reda Mohamed Hamou; Abdelmalek Amine; Ahmed Chaouki Lokbani; | Cluster Computing | 2020-01-01 |
1405 | Two-Level Text Summarization Using Topic Modeling Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Since the dawn of the Internet, the size of textual data has been steadily growing, every single day, due to frequent usage of digital libraries, social media, and online search … |
Dhannuri Saikumar; P. Subathra; | 2020-01-01 | |
1406 | SuDocu: Summarizing Documents By Example Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text document summarization refers to the task of producing a brief representation of a document for easy human consumption. Existing text summarization techniques mostly focus on … |
Anna Fariha; Matteo Brucato; Peter J. Haas; Alexandra Meliou; | Proc. VLDB Endow. | 2020-01-01 |
1407 | An Application of Zipf’s Law for Prose and Verse Corpora Neutrality for Hindi and Marathi Languages Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Availability of the text in different languages has become possible, as almost all websites have offered multilingual option. Hindi is considered as official language in one of … |
Prafulla B. Bafna; Jatinderkumar R.; | International Journal of Advanced Computer Science and … | 2020-01-01 |
1408 | A Decomposition-based Multi-objective Optimization Approach for Extractive Multi-document Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Currently, due to the overflow of textual information on the Internet, automatic text summarization methods are becoming increasingly important in many fields of knowledge. … |
Jesus M. Sanchez-Gomez; Miguel A. Vega-Rodríguez; Carlos J. Pérez; | Appl. Soft Comput. | 2020-01-01 |
1409 | Combining Temporal Event Relations and Pre-Trained Language Models for Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, we introduce an innovative high performing deep learning architecture for text summarization using pre-trained language models. Language model (LM) pre-training has … |
Divyanshu Daiya; | 2020 19th IEEE International Conference on Machine Learning … | 2020-01-01 |
1410 | Generating Myanmar News Headlines Using Recursive Neural Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization in the form of Headline prediction for written articles becomes a popular research recently. This paper presents a headline prediction model using Recursive … |
Yamin Thu; Win Pa Pa; | 2020 IEEE Conference on Computer Applications(ICCA) | 2020-01-01 |
1411 | Improving Abstractive Summarization Via Dilated Convolution Related Papers Related Patents Related Grants Related Venues Related Experts View |
Dawei Jin; Ruizhi Kang; Hongjun Zhang; Wening Hao; Gang Chen; | 2020-01-01 | |
1412 | Subword Neural Language Generation with Unlikelihood Training Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various … |
Salahuddin Muhammad Iqbal; Dae-Ki Kang; | 2020-01-01 | |
1413 | An Improved Template Representation-based Transformer for Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization plays an important role in various NLP applications. Using templates with generation methods is an effective way to address abstractive summarization. However, … |
Jiaming Sun; Yunli Wang; Zhoujun Li; | 2020 International Joint Conference on Neural Networks … | 2020-01-01 |
1414 | A Semantic Approach to Extractive Multi-document Summarization: Applying Sentence Expansion for Tuning of Conceptual Densities IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Today, due to a vast amount of textual data, automated extractive text summarization is one of the most common and practical techniques for organizing information. Extractive … |
Mohammad Bidoki; Mohammad R. Moosavi; Mostafa Fakhrahmad; | Inf. Process. Manag. | 2020-01-01 |
1415 | TF-BiLSTMS2S: A Chinese Text Summarization Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this paper, a method of text summarization based on deep learning is proposed. The method combines the topic information into the Bidirectional LSTM sequence to sequence model … |
Caiquan Xiong; Zhuang Wang; Li Shen; Na Deng; | 2020-01-01 | |
1416 | A Hierarchical Self-attentive Neural Extractive Summarizer Via Reinforcement Learning (HSASRL) IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, deep neural extractive-based summarization approaches have achieved vast popularity over conventional approaches. However, previously proposed neural … |
Farida Mohsen; Jiayang Wang; Kamal Al-Sabahi; | Applied Intelligence | 2020-01-01 |
1417 | Enhancement of Single Document Text Summarization Using Reinforcement Learning with Non-Deterministic Rewards Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A text summarization system generates short and brief summaries of original document for given user queries. The machine generated summaries uses information retrieval techniques … |
K. Karpagam; A. Saradha; K. Manikandan; K. Madusudanan; | International Journal of Information Technology and … | 2020-01-01 |
1418 | Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recent advances in natural language processing have enabled automation of a wide range of tasks, including machine translation, named entity recognition, and sentiment analysis. … |
AMANUEL ALAMBO et. al. | 2020 IEEE International Conference on Big Data (Big Data) | 2020-01-01 |
1419 | Heuristic Algorithm for Resolving Pronominal Anaphora in Hindi Dialects Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Artificial intelligence is a necessity for today’s realistic world knowledge. The facts hidden by the anaphoric expressions can be revealed by anaphora resolution only. The … |
Seema Mahato; Ani Thomas; Neelam Sahu; | 2020-01-01 | |
1420 | An Ensemble Approach for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Voluminous information spread with an ever-increasing number of articles, links and videos to choose from have made us struggle to make informed decisions quickly. The importance … |
Prabhjot Singh; Prateek Chhikara; Jasmeet Singh; | 2020 International Conference on Emerging Trends in … | 2020-01-01 |
1421 | The Purpose of Bellman-Ford Algorithm to Summarize The Multiple Scientific Indonesian Journal Articles Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text is a one of huge type data in the big data era today. It can be processed to be valuable information with Natural Language Processing approach, such as Automated Text … |
DIAN SA’ADILLAH MAYLAWATI et. al. | 2020 6th International Conference on Wireless and … | 2020-01-01 |
1422 | Application of Text Summarization Technology in Human Resource Management Informatization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the era of big data, great changes have taken place in the internal and external environment of enterprises. Human resource management is the core of enterprises. In the era of … |
Tao Liu; | Proceedings of the 2020 Conference on Artificial … | 2020-01-01 |
1423 | Latent Semantic Analysis in Automatic Text Summarization: A State of The Art Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mehala N; Tapas Guha; | 2020-01-01 | |
1424 | Evaluation of Content Compaction in Assamese Language Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is the task of condensing the input text documents into a shorter version by retaining the overall meaning and information of the original document. Though … |
Nomi Baruah; Shikhar Kr. Sarma; Surajit Borkotokey; | Procedia Computer Science | 2020-01-01 |
1425 | A Bengali Text Generation Approach in Context of Abstractive Text Summarization Using RNN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is one of the mentionable research areas of natural language processing. The amount of data is increasing rapidly, and the necessity of understanding … |
Sheikh Abujar; Abu Kaisar Mohammad Masum; Md. Sanzidul Islam; Fahad Faisal; Syed Akhter Hossain; | 2020-01-01 | |
1426 | Query-based Abstractive Summarization Model Using Sentence Ranking Scores and Graph Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ko, Youngjoong; | 2020-01-01 | |
1427 | A Two-step Abstractive Summarization Model with Asynchronous and Enriched-information Decoding Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Most sequence-to-sequence abstractive summarization models generate the summaries based on the source article and the generated words, but they often neglect the future … |
Shuaimin Li; Jungang Xu; | Neural Computing and Applications | 2020-01-01 |
1428 | Neural Attention Model with Keyword Memory for Abstractive Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive summarization is the task of creating summaries by generating a set of novel sentences based on the information extracted from the original document, while most of … |
Yun Seok Choi; Dahae Kim; Jee-Hyong Lee; | Concurrency and Computation: Practice and Experience | 2020-01-01 |
1429 | Multi-task Learning for Abstractive Text Summarization with Key Information Guide Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural networks based on the attentional encoder-decoder model have good capability in abstractive text summarization. However, these models are hard to be controlled in the … |
Weiran Xu; Chenliang Li; Minghao Lee; Chi Zhang; | EURASIP Journal on Advances in Signal Processing | 2020-01-01 |
1430 | Query Focused Abstractive Summarization Via Incorporating Query Relevance and Transfer Learning with Transformer Models IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the Query Focused Abstractive Summarization (QFAS) task, the goal is to generate abstractive summaries from the source document that are relevant to the given query. In this … |
Md. Tahmid Rahman Laskar; Enamul Hoque; Xiangji Huang; | 2020-01-01 | |
1431 | Approaches and Trends of Automatic Bangla Text Summarization: Challenges and Opportunities Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As long as the internet user is increasing, online electronic content is growing proportionally irrespective of languages. A lot of research works on English text summarization … |
Md. Majharul Haque; Suraiya Pervin; Anowar Hossain; Zerina Begum; | Int. J. Technol. Diffusion | 2020-01-01 |
1432 | ArA*summarizer: An Arabic Text Summarization System Based on Subtopic Segmentation and Using An A* Algorithm for Reduction Related Papers Related Patents Related Grants Related Venues Related Experts View |
Belahcene Bahloul; Hassina Aliane; Mohamed Benmohammed; | Expert Syst. J. Knowl. Eng. | 2020-01-01 |
1433 | Belief Propagation for Maximum Coverage on Weighted Bipartite Graph and Application to Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We study text summarization from the viewpoint of maximum coverage problem. In graph theory, the task of text summarization is regarded as maximum coverage problem on bipartite … |
Hiroki Kitano; Koujin Takeda; | ArXiv | 2020-01-01 |
1434 | Generating Summaries Through Unigram and Bigram: Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Thisarticledescribesanewmethodforgeneratingextractivesummariesdirectlyviaunigramand … |
Nesreen Mohammad Alsharman; Inna Pivkina; | Int. J. Inf. Technol. Web Eng. | 2020-01-01 |
1435 | Japanese Abstractive Text Summarization Using BERT Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this study, we developed an automatic abstractive text summarization algorithm in Japanese using a neural network. We used a sequence-to-sequence encoder-decoder model for … |
Yuuki Iwasaki; Akihiro Yamashita; Yoko Konno; Katsushi Matsubayashi; | Advances in Science, Technology and Engineering Systems … | 2020-01-01 |
1436 | Comprehensive Survey on Abstractive Text Summarization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Paritosh Marathe; | International Journal of Engineering Research and | 2020-01-01 |
1437 | Leveraging Natural Language Processing Applications Using Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The enormous increase of information along with the computational abilities of machines created innovative applications in natural language processing by invoking machine learning … |
Janjanam Prabhudas; C. H. Pradeep Reddy; | 2020-01-01 | |
1438 | An Evaluation of Word Frequency Techniques for Text Summarization Using Sentiment Analysis Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Digital data has become an important aspect of machine learning and is present in huge volumes on the internet. To use this data efficiently, data handling and processing … |
Shikha Shandilya; Nidhi Bansal; Shuchi Mala; | 2020 10th International Conference on Cloud Computing, Data … | 2020-01-01 |
1439 | Text Summarization Method Based on Double Attention Pointer Network IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: A good document summary should summarize the core content of the text. Research on automatic text summarization attempts to solve this problem. The encoder-decoder model is widely … |
Zhixin Li; Zhi Peng; Suqin Tang; Canlong Zhang; Huifang Ma; | IEEE Access | 2020-01-01 |
1440 | A Syntax-Augmented and Headline-Aware Neural Text Summarization Method Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the advent of the information age, excessive information collection leads to information overload. Automatic text summarization technology has become an effective way to … |
Jingwei Cheng; Fu Zhang; Xuyang Guo; | IEEE Access | 2020-01-01 |
1441 | Extractive Text Summarization from Web Pages Using Selenium and TF-IDF Algorithm IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To obtain an overview of the content present in numerous documents, is a time-consuming task. Similarly, searching for specific information online, from multiple websites and … |
K Usha Manjari; Syed Rousha; Dasi Sumanth; J Sirisha Devi; | 2020 4th International Conference on Trends in Electronics … | 2020-01-01 |
1442 | A Two-Stage Transformer-Based Approach for Variable-Length Abstractive Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This study proposes a two-stage method for variable-length abstractive summarization. This is an improvement over previous models, in that the proposed approach can simultaneously … |
Ming-Hsiang Su; Chung-Hsien Wu; Hao-Tse Cheng; | IEEE/ACM Transactions on Audio, Speech, and Language … | 2020-01-01 |
1443 | An Assessment of Sentence Simplification Methods in Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The unprecedented growth of textual content on the Web made essential the development of automatic or semi-automatic techniques to help people to find valuable information in such … |
Rafaella F. Vale; Rafael Dueire Lins; Rafael Ferreira; | Proceedings of the ACM Symposium on Document Engineering … | 2020-01-01 |
1444 | Conceptual Persian Text Summarizer: A New Model in Continuous Vector Space Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Traditional methods of summarization are not cost-effective and possible today. Extractive summarization is a process that helps to extract the most important sentences from a … |
Mohammad Khademi; Mohammad Fakhredanesh; Seyed Hoseini; | The International Arab Journal of Information Technology | 2020-01-01 |
1445 | Comprehensive Document Summarization with Refined Self-Matching Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Under the constraint of memory capacity of the neural network and the document length, it is difficult to generate summaries with adequate salient information. In this work, the … |
Biqing Zeng; Ruyang Xu; Heng Yang; Zibang Gan; Wu Zhou; | Applied Sciences | 2020-01-01 |
1446 | Semantic Similarity and Text Summarization Based Novelty Detection IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Current web crawlers search the queries at very high speed, but the problem of novelty detection or redundant information still persists. It consumes precious time and memory of … |
Sushil Kumar; Komal Kumar Bhatia; | SN Applied Sciences | 2020-01-01 |
1447 | Automatic Text Summarization: A State-of-the-Art Review IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Despite the progress that has been achieved in over 50 years of research, automatic text summarization systems are still far from perfect, posing many challenges to the … |
Oleksandra Klymenko; Daniel Braun; Florian Matthes; | 2020-01-01 | |
1448 | Text Summarization By Hybridization of Hypergraphs and Hill Climbing Technique Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization (ATS) is an application of natural language processing (NLP). It is the process of compressing the given text to create a summary. The challenge is … |
Hemamalini Siranjeevi; Swaminathan Venkatraman; Kannan Krithivasan; | 2020-01-01 | |
1449 | Abstractive Text Summarization and Unsupervised Text Classifier Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this day and age, as the Internet gets increasingly cluttered for content, the comprehension of generated huge texts is growingly becoming a source of major inconvenience for a … |
Akanksha Shrivastava; Saurabh Bilgaiyan; | 2020-01-01 | |
1450 | Using Argument Mining for Legal Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Argument mining, a subfield of natural language processing and text mining, is a process of extracting argumentative text portions and identifying the role the selected texts … |
Huihui Xu; Jaromír Šavelka; Kevin D. Ashley; | 2020-01-01 | |
1451 | Grouping Sentences As Better Language Unit for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Most existing methods for extractive text summarization aim to extract important sentences with statistical or linguistic techniques and concatenate these sentences as a summary. … |
Mengyun Cao; Hai Zhuge; | Future Gener. Comput. Syst. | 2020-01-01 |
1452 | Attention History-based Attention for Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Recently, encoder-decoder model using attention has shown meaningful results in the abstractive summarization tasks. In the attention mechanism, the attention distribution is … |
HyunSoo Lee; YunSeok Choi; Jee-Hyong Lee; | Proceedings of the 35th Annual ACM Symposium on Applied … | 2020-01-01 |
1453 | Evaluation of State-of-the-Art Paraphrase Identification and Its Application to Automatic Plagiarism Detection IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Paraphrase identification is a natural language processing (NLP) problem that involves the determination of whether two text segments have the same meaning. Various NLP … |
Alaa Saleh Altheneyan; Mohamed El Bachir Menai; | Int. J. Pattern Recognit. Artif. Intell. | 2020-01-01 |
1454 | Evaluation and Summarization of Student Feedback Using Sentiment Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Educational data mining facilitates educational institutions to discover useful patterns and apply them to improve the overall quality of education. Analysing student feedback may … |
Neeraj Sharma; Vaibhav Jain; | 2020-01-01 | |
1455 | Abstractive Social Media Text Summarization Using Selective Reinforced Seq2Seq Attention Model IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive text summarization aims to generate a brief version of a given sentence while attempting to express its main meaning. Although some models based on the … |
Zeyu Liang; Junping Du; Chaoyang Li; | Neurocomputing | 2020-01-01 |
1456 | Enhanced Language Modeling with Proximity and Sentence Relatedness Information for Extractive Broadcast News Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The primary task of extractive summarization is to automatically select a set of representative sentences from a text or spoken document that can concisely express the most … |
Shih-Hung Liu; Kuan-Yu Chen; Berlin Chen; | ACM Transactions on Asian and Low-Resource Language … | 2020-01-01 |
1457 | A Comparative Study of Classifiers for Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization (ATS) is a widely used approach. Through the years, various techniques have been implemented to produce the summary. An extractive summary is a … |
Anshuman Pattanaik; Sanjeevani Subhadra Mishra; Madhabananda Das; | 2020-01-01 | |
1458 | Abstractive Text Summarization Using Seq2seq Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Knowledge is power and information is liberating. As the quote says, in today’s world the information is available in abundance and a lot of new possibilities can be explored from … |
S Keerthana; R Venkatesan; | International Journal of Computer Applications | 2020-01-01 |
1459 | Opinion Mining with Reviews Summarization Based on Clustering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization can be used in recommendation systems to present useful texts obtained from the available comments and texts. For summarization, a human reads all of … |
Shabnam Bagheri Marzijarani; Hedieh Sajedi; | International Journal of Information Technology | 2020-01-01 |
1460 | Extractive Multi-Document Text Summarization By Using Binary Particle Swarm Optimization Related Papers Related Patents Related Grants Related Venues Related Experts View |
Archana Potnurwar; | Bioscience Biotechnology Research Communications | 2020-01-01 |
1461 | NMF Ensembles? Not for Text Summarization! Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Non-negative Matrix Factorization (NMF) has been used for text analytics with promising results. Instability of results arising due to stochastic variations during initialization … |
Alka Khurana; Vasudha Bhatnagar; | 2020-01-01 | |
1462 | TRAINING VIETNAMESE TEXT SUMMARIZATION MODELS FROM A BIG DATA COLLECTION Related Papers Related Patents Related Grants Related Venues Related Experts View |
Ti Hon Nguyen; Ngoc Han Nguyen Thi; The Phi Pham; Thanh Nghi Do; | KỶ YẾU HỘI NGHỊ KHOA HỌC CÔNG NGHỆ QUỐC GIA LẦN THỨ XIII … | 2020-01-01 |
1463 | Extractive Text Summarization Models for Urdu Language IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the recent few years, a lot of advancement has been made in Urdu linguistics. There are many portals and news websites that are generating a huge amount of data every day. … |
ALI NAWAZ et. al. | Inf. Process. Manag. | 2020-01-01 |
1464 | An HCI Approach to Extractive Text Summarization: Selecting Key Sentences Based on User Copy Operations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is a very complex problem. Despite being intensively researched, automatic summaries are still considered to be of lower quality than manual … |
Ilan Kirsh; Mike Joy; | 2020-01-01 | |
1465 | Development Of Crossword Puzzles In The Learning Of Explanatory Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This research is based on Indonesian language learning that has not been effective yet, so the result of learned is not optimal yet, to overcome this problem, the researcher … |
Yunita Lestari; Nugraheti Sismulyasih Sb; | The Elementary School Teacher | 2020-01-01 |
1466 | Extractive Text Summarization System for News Texts Related Papers Related Patents Related Grants Related Venues Related Experts View |
Fahrettin Horasan; Burhan Bilen; | International Journal of Applied Mathematics, Electronics … | 2020-01-01 |
1467 | Automatic Text Summarization Using Fuzzy Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is an approach to summarize the original document with better efficiency than human. Mining prominent words from the original document and connecting those to … |
Bharti Sharma; Nitika Katyal; Vishant Kumar; Amit Lathwal; | 2020-01-01 | |
1468 | Text Summarization with Different Encoders for Pointer Generator Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The ever-growing increase of documents has compelled the need of text summarization. In the past, deep learning models have shown state-of-the-art results for text summarization. … |
Minakshi Tomer; Manoj Kumar; | 2020-01-01 | |
1469 | Deep Extractive Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With introduction of deep learning techniques their has been an increase in intelligent classification of text in many applications. Advances in automatic text summarization using … |
Rupal Bhargava; Yashvardhan Sharma; | Procedia Computer Science | 2020-01-01 |
1470 | Deep Text Summarization Using Generative Adversarial Networks in Indian Languages IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive Text Summarization (ATS) is a task of capturing information from different sources and condense it such that, content is represented well and there is no loss of … |
Rupal Bhargava; Gargi Sharma; Yashvardhan Sharma; | Procedia Computer Science | 2020-01-01 |
1471 | Exploring The Implementation of Automatic Text Summarization in Online Learning Setting Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summatization is a technique of text mining which is a field of natural language processing. It summarizes a long text file or document automatically into several … |
Agus Wedi; Saida Ulfa; Ashar Pakkawaru; Rex Bringula; | 2020-01-01 | |
1472 | Text Summarization As A Multi-objective Optimization Task: Applying Harmony Search to Extractive Multi-Document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Today, automated extractive text summarization is one of the most common techniques for organizing information. In extractive summarization, the most appropriate sentences are … |
M Bidoki; M Fakhrahmad; M R Moosavi; | The Computer Journal | 2020-01-01 |
1473 | Amharic Open Information Extraction with Syntactic Sentence Simplification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Open Information Extraction (OIE) is the process of discovering domain-independent relations from natural language text. It has recently received increased attention and been … |
Seble Girma; Yaregal Assabie; | 2020-01-01 | |
1474 | Effect of Semantic Content Generalization on Pointer Generator Network in Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic content generalization is a method for text summarization that reduces the difficulty of training of neural networks by replacing some phrases such as named entities with … |
Yixuan Wu; Kei Wakabayashi; | Proceedings of the 22nd International Conference on … | 2020-01-01 |
1475 | Exploiting Siamese Neural Networks on Short Text Similarity Tasks for Multiple Domains and Languages Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Semantic textual similarity algorithms are essential to several natural language processing tasks as clustering documents and text summarization. Many shared tasks regarding this … |
João Vitor Andrioli de Souza; Lucas Emanuel Silva e Oliveira; Yohan Bonescki Gumiel; Deborah Ribeiro Carvalho; Claudia Maria Cabral Moro; | 2020-01-01 | |
1476 | How to Interact and Change? Abstractive Dialogue Summarization with Dialogue Act Weight and Topic Change Info Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Conventional sequence-to-sequence frameworks in neural abstractive summarization treat every document as a single topic text without interaction, so the results are often … |
Jiasheng Di; Xiao Wei; Zhenyu Zhang; | 2020-01-01 | |
1477 | Comparative Study on Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper represents a comparative study and gives an overview on some of the great research work done on abstractive text summarization. Getting a gist part from a large text … |
Md. Ashraful Islam Talukder; Sheikh Abujar; Abu Kaisar Mohammad Masum; Sharmin Akter; Syed Akhter Hossain; | 2020 11th International Conference on Computing, … | 2020-01-01 |
1478 | Topic-sensitive Neural Headline Generation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural models are being widely applied for text summarization, including headline generation, and are typically trained using a set of document-headline pairs. In a large document … |
Lei Xu; Ziyun Wang; Zhiyuan Liu; Maosong Sun; | Science China Information Sciences | 2020-01-01 |
1479 | Text Summarization and Classification of Conversation Data Between Service Chatbot and Customer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In any business, a humongous amount of data is generated within each fraction of a second by each and every software application. However, processing this voluminous data is a … |
TANMAYEE BEHERE et. al. | 2020 Fourth World Conference on Smart Trends in Systems, … | 2020-01-01 |
1480 | Global Word Sense Disambiguation of Polysemous Words in Telugu Language Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Word Sense Disambiguation (WSD) is a significant issue in Natural Language Processing (NLP). WSD refers to the capacity of recognizing the correct sense of a word in a given … |
Suneetha Eluri; Vasu Kumar Pilli; | Regular | 2020-01-01 |
1481 | Peringkasan Multi Dokumen Berita Dengan Pemilihan Kalimat Utama Berbasis Algoritma Cluster Importance Dengan Mempertimbangkan Posisi Kalimat Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstrak Peringkasan teks merupakan salah satu cara untuk mengurangi suatu dimensi dokumen yang besar untuk mendapatkan informasi penting dari dokumen tersebut. Berita adalah salah … |
Syadza Anggraini; Nur Hayatin; Gita Indah Marthasari; | 2020-01-01 | |
1482 | Candidate Sentence Selection for Extractive Text Summarization IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is a process of generating a brief version of documents by preserving the fundamental information of documents as much as possible. Although most of the text … |
Begum Mutlu; Ebru Akcapinar Sezer; Muhammet Ali Akcayol; | Inf. Process. Manag. | 2020-01-01 |
1483 | Towards Generating Query to Perform Query Focused Abstractive Summarization Using Pre-trained Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Query Focused Abstractive Summarization (QFAS) represents an abstractive summary from the source document based on a given query. To measure the performance of abstractive … |
D. Abdullah; Yllias Chali; | International Conference on Natural Language Generation | 2020-01-01 |
1484 | A HYBRID APPROACH FOR TEXT SUMMARIZATION Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shabbir Sidhpurwala; Saiyam Jain; Sushma Verma; | Ethics and Information Technology | 2020-01-01 |
1485 | Improving Text Summarization Using Ensembled Approach Based on Fuzzy with LSTM IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive text summarization using attentional recurrent neural network (sequence-to-sequence) models have proven to be very effective. In this paper, a novel hybrid approach is … |
Minakshi Tomer; Manoj Kumar; | Arabian Journal for Science and Engineering | 2020-01-01 |
1486 | A Hierarchical Bidirectional LSTM Sequence Model for Extractive Text Summarization in Electric Power Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: With the increasing volume of documents in electric power systems, it is urgent and necessary for electric power systems managers to efficiently analyze the massive documents and … |
Wei Jiang; Yunfeng Zou; Ting Zhao; Qiang Zhang; Yinglong Ma; | 2020 13th International Symposium on Computational … | 2020-01-01 |
1487 | Automatic Text Summarization Based on Selective OOV Copy Mechanism with BERT Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View |
Tae-Seok Lee; Seung-Shik Kang; | 2020-01-01 | |
1488 | Developing A New Approach to Summarize Arabic Text Automatically Using Syntactic and Semantic Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Due to the wide spread information and the diversity of its sources, there is a need to produce an accurate text summary with the least time and effort. This summary must preserve … |
Amal Alkhudari; | International journal of engineering and technology | 2020-01-01 |
1489 | Query-based Single Document Summarization Using Hybrid Semantic and Graph-based Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In this era of digitization, a plethora of information, spanning a multitude of themes, is available worldwide. The demand for query focused text summarization is growing rapidly … |
Samridhi Murarka; Akshat Singhal; | 2020 International Conference on Advances in Computing, … | 2020-01-01 |
1490 | ViMs: A High-quality Vietnamese Dataset for Abstractive Multi-document Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Automatic text summarization is important in this era due to the exponential growth of documents available on the Internet. In the Vietnamese language, VietnameseMDS is the only … |
NHI-THAO TRAN et. al. | Language Resources and Evaluation | 2020-01-01 |
1491 | Text Analysis on Health Product Reviews Using R Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the social media, product reviews contain of text, emoticon, numbers and symbols that hard to identify the text summarization. Text analytics is one of the key techniques in … |
Nasibah Husna Mohd Kadir; Sharifah Aliman; | Indonesian Journal of Electrical Engineering and Computer … | 2020-01-01 |
1492 | DocEng’2020 Competition on Extractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The DocEng’2020 Competition on Extractive Text Summarization assessed the performance of six new methods and fourteen classical algorithms for extractive text sumarization. The … |
Rafael Dueire Lins; Rafael Ferreira Leite de Mello; Steven J. Simske; | Proceedings of the ACM Symposium on Document Engineering … | 2020-01-01 |
1493 | AUTOMATIC HINDI TEXT SUMMARIZATION USING SELECTION AND ELIMINATION APPROACH Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, the shoot up of web information has required to make intensive research in the field of automatic text summarization which is the part of the Natural Language … |
Mili Supreet; Kanu Goel; Madhuri Gupta; | 2020-01-01 | |
1494 | Review of Techniques for Automatic Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summarization refers to the process of reducing the textual components such as words and sentences but conveying most of the information in the input text. Research in … |
B. SHIVA PRAKASH et. al. | 2020-01-01 | |
1495 | Comparative Analysis of Neural Models for Abstractive Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Abstractive text summarization is the task of generating the summary of text documents like humans do. It’s completely laborious and time taking process to summarize the lengthy … |
Heena Kumari; Sunita Sarkar; Vikrant Rajput; Arindam Roy; | 2020-01-01 | |
1496 | Evaluation of Improved Components of AMIS Project for Speech Recognition, Machine Translation and Video/Audio/Text Summarization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: To evaluate a system that automatically summarizes video files (image and audio) and text, how the system works, and the quality of the results should be considered. With this … |
ARITZ BADIOLA et. al. | 2020-01-01 | |
1497 | Extractive Arabic Text Summarization Using Modified PageRank Algorithm IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper proposed an approach for Arabic text summarization. Text summarization is one of the natural language processing’s applications which is used for reducing the original … |
Reda Elbarougy; Gamal Behery; Akram El Khatib; | Egyptian Informatics Journal | 2020-01-01 |
1498 | Unsupervised Multi-Document Abstractive Summarization Using Recursive Neural Network with Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Text summarization is an active field of research with a goal to provide short and meaningful gists from large amount of text documents. Extractive text summarization methods have … |
Aniv Chakravarty; Jagadish S. Kallimani; | Journal of Computational and Theoretical Nanoscience | 2020-01-01 |
1499 | A Combined Model for Extractive and Abstractive Summarization Based on Transformer Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Summary generates by summarizing automatically main information from the critical sentences of the article. The traditional method of generating text summarization uses extractive … |
Xin Liu; Liutong Xu; | 2020-01-01 | |
1500 | Improving Abstractive Summarization with Iterative Representation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In the neural abstractive summarization field, comprehensive document representation and summary embellishment are two major challenges. To tackle the above problems, we propose … |
Jinpeng Li; Chuang Zhang; Xiaojun Chen; Yanan Cao; Ruipeng Jia; | 2020 International Joint Conference on Neural Networks … | 2020-01-01 |