Paper Digest: Recent Papers on Question Answering
Paper Digest Team extracted all recent Question Answering 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. Based in New York, Paper Digest is dedicated to producing high-quality text analysis results that people can acturally use on a daily basis. Since 2018, we have been serving users across the world with a number of exclusive services on ranking, search, tracking and automatic literature review.
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TABLE 1: Paper Digest: Recent Papers on Question Answering
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | CC-Riddle: A Question Answering Dataset of Chinese Character Riddles Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Chinese character riddle dataset covering the majority of common simplified Chinese characters by crawling riddles from the Web and generating brand new ones. |
Fan Xu; Yunxiang Zhang; Xiaojun Wan; | arxiv-cs.CL | 2022-06-28 |
| 2 | Consistency-preserving Visual Question Answering in Medical Imaging Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel loss function and corresponding training procedure that allows the inclusion of relations between questions into the training process. |
Sergio Tascon-Morales; Pablo Márquez-Neila; Raphael Sznitman; | arxiv-cs.CV | 2022-06-27 |
| 3 | Contextual Embedding and Model Weighting By Fusing Domain Knowledge on Biomedical Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a contextual embedding method that combines open-domain QA model \aoa and \biobert model pre-trained on biomedical domain data. |
Yuxuan Lu; Jingya Yan; Zhixuan Qi; Zhongzheng Ge; Yongping Du; | arxiv-cs.CL | 2022-06-26 |
| 4 | Evaluation of Semantic Answer Similarity Metrics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose cross-encoder augmented bi-encoder and BERTScore models for semantic answer similarity, trained on a new dataset consisting of name pairs of US-American public figures. |
Farida Mustafazade; Peter Ebbinghaus; | arxiv-cs.CL | 2022-06-25 |
| 5 | OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a new task, Open-Book TOD (OB-TOD), which combines TOD with QA task and expand external knowledge sources to include both explicit knowledge sources (e.g., the Web) and implicit knowledge sources (e.g., pre-trained language models). |
Miaoran Li; Baolin Peng; Jianfeng Gao; Zhu Zhang; | arxiv-cs.CL | 2022-06-24 |
| 6 | From Shallow to Deep: Compositional Reasoning Over Graphs for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: It is effortless for human but challenging for machines. In this paper, we propose a Hierarchical Graph Neural Module Network (HGNMN) that reasons over multi-layer graphs with neural modules to address the above issues. |
Zihao Zhu; | arxiv-cs.CV | 2022-06-24 |
| 7 | Looking for Related Discussions on GitHub Discussions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address the problem of detecting related posts in GitHub Discussions. |
MARCIA LIMA et. al. | arxiv-cs.SE | 2022-06-23 |
| 8 | Surgical-VQA: Visual Question Answering in Surgical Scenes Using Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we design a Surgical-VQA task that answers questionnaires on surgical procedures based on the surgical scene. |
Lalithkumar Seenivasan; Mobarakol Islam; Adithya K Krishna; Hongliang Ren; | arxiv-cs.CV | 2022-06-22 |
| 9 | COREQQA — A COmpliance REQuirements Understanding Using Question Answering Tool Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce COREQQA, a tool for assisting requirements engineers in acquiring a better understanding of compliance requirements by means of automated Question Answering. |
Sallam Abualhaija; Chetan Arora; Lionel Briand; | arxiv-cs.SE | 2022-06-21 |
| 10 | WikiDoMiner: Wikipedia Domain-specific Miner Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce WikiDoMiner, a tool for automatically generating domain-specific corpora by crawling Wikipedia. |
Saad Ezzini; Sallam Abualhaija; Mehrdad Sabetzadeh; | arxiv-cs.SE | 2022-06-21 |
| 11 | Questions Are All You Need to Train A Dense Passage Retriever Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce ART, a new corpus-level autoencoding approach for training dense retrieval models that does not require any labeled training data. |
DEVENDRA SINGH SACHAN et. al. | arxiv-cs.CL | 2022-06-21 |
| 12 | SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a two-stage QA system based on Sentence-BERT (SBERT) using multiple negatives ranking (MNR) loss combined with BM25. |
Nhung Thi-Hong Nguyen; Phuong Phan-Dieu Ha; Luan Thanh Nguyen; Kiet Van Nguyen; Ngan Luu-Thuy Nguyen; | arxiv-cs.CL | 2022-06-20 |
| 13 | EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In the context of language-conditioned RL, the abstraction and generalisation properties of the language input provide opportunities for more efficient ways of shaping the reward. In this paper, we leverage this idea and propose an automated reward shaping method where the agent extracts auxiliary objectives from the general language goal. |
Thomas Carta; Sylvain Lamprier; Pierre-Yves Oudeyer; Olivier Sigaud; | arxiv-cs.CL | 2022-06-20 |
| 14 | Partisan US News Media Representations of Syrian Refugees Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyze 47,388 articles from the online US media about Syrian refugees to detail differences in reporting between left- and right-leaning media. We use various NLP techniques to understand these differences. |
KEYU CHEN et. al. | arxiv-cs.SI | 2022-06-17 |
| 15 | Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Most existing approaches cannot provide an interpretable reasoning process to illustrate how these models arrive at an answer. In this paper, we propose a Question Decomposition method based on Abstract Meaning Representation (QDAMR) for multi-hop QA, which achieves interpretable reasoning by decomposing a multi-hop question into simpler sub-questions and answering them in order. |
Zhenyun Deng; Yonghua Zhu; Yang Chen; Michael Witbrock; Patricia Riddle; | arxiv-cs.CL | 2022-06-16 |
| 16 | GAAMA 2.0: An Integrated System That Answers Boolean and Extractive Questions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a multilingual machine reading comprehension system and front-end demo that handles boolean questions by providing both a YES/NO answer and highlighting supporting evidence, and handles extractive questions by highlighting the answer in the passage. |
SCOTT MCCARLEY et. al. | arxiv-cs.CL | 2022-06-16 |
| 17 | An Open-Domain QA System for E-Governance Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The paper presents an open-domain Question Answering system for Romanian, answering COVID-19 related questions. |
RADU ION et. al. | arxiv-cs.CL | 2022-06-16 |
| 18 | A Numerical Reasoning Question Answering System with Fine-grained Retriever and The Ensemble of Multiple Generators for FinQA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we propose a numerical reasoning question answering system to answer numerical reasoning questions among financial text and table data sources, consisting of a retriever module, a generator module, and an ensemble module. |
BIN WANG et. al. | arxiv-cs.CL | 2022-06-16 |
| 19 | MixGen: A New Multi-Modal Data Augmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present MixGen: a joint data augmentation for vision-language representation learning to further improve data efficiency. |
XIAOSHUAI HAO et. al. | arxiv-cs.CV | 2022-06-16 |
| 20 | Zero-Shot Video Question Answering Via Frozen Bidirectional Language Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, a promising approach adapts frozen autoregressive language models pretrained on Web-scale text-only data to multi-modal inputs. In contrast, we here build on frozen bidirectional language models (BiLM) and show that such an approach provides a stronger and cheaper alternative for zero-shot VideoQA. |
Antoine Yang; Antoine Miech; Josef Sivic; Ivan Laptev; Cordelia Schmid; | arxiv-cs.CV | 2022-06-16 |
| 21 | Test-Time Adaptation for Visual Document Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose DocTTA, a novel test-time adaptation approach for documents that leverages cross-modality self-supervised learning via masked visual language modeling as well as pseudo labeling to adapt models learned on a \textit{source} domain to an unlabeled \textit{target} domain at test time. |
Sayna Ebrahimi; Sercan O. Arik; Tomas Pfister; | arxiv-cs.CV | 2022-06-14 |
| 22 | LAVENDER: Unifying Video-Language Understanding As Masked Language Modeling Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore a unified VidL framework LAVENDER, where Masked Language Modeling (MLM) is used as the common interface for all pre-training and downstream tasks. |
LINJIE LI et. al. | arxiv-cs.CV | 2022-06-14 |
| 23 | Task Transfer and Domain Adaptation for Zero-Shot Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Pretrained language models have shown success in various areas of natural language processing, including reading comprehension tasks. |
XIANG PAN et. al. | arxiv-cs.CL | 2022-06-14 |
| 24 | CHQ-Summ: A Dataset for Consumer Healthcare Question Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: One way to address this challenge is to summarize the questions and distill the key information of the original question. To address this issue, we introduce a new dataset, CHQ-Summ that contains 1507 domain-expert annotated consumer health questions and corresponding summaries. |
Shweta Yadav; Deepak Gupta; Dina Demner-Fushman; | arxiv-cs.CL | 2022-06-13 |
| 25 | Ask to Know More: Generating Counterfactual Explanations for Fake Claims Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose elucidating fact checking predictions using counterfactual explanations to help people understand why a specific piece of news was identified as fake. |
Shih-Chieh Dai; Yi-Li Hsu; Aiping Xiong; Lun-Wei Ku; | arxiv-cs.CL | 2022-06-10 |
| 26 | Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore automatically generated questions as personalized feedback in an ITS. |
DEVANG KULSHRESHTHA et. al. | arxiv-cs.CL | 2022-06-08 |
| 27 | Dual-Key Multimodal Backdoors for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that multimodal networks are vulnerable to a novel type of attack that we refer to as Dual-Key Multimodal Backdoors. |
Matthew Walmer; Karan Sikka; Indranil Sur; Abhinav Shrivastava; Susmit Jha; | cvpr | 2022-06-07 |
| 28 | From Representation to Reasoning: Towards Both Evidence and Commonsense Reasoning for Video Question-Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To facilitate deeper video understanding towards video reasoning, we present the task of Causal-VidQA, which includes four types of questions ranging from scene description (description) to evidence reasoning (explanation) and commonsense reasoning (prediction and counterfactual). |
Jiangtong Li; Li Niu; Liqing Zhang; | cvpr | 2022-06-07 |
| 29 | CViL: Cross-Lingual Training of Vision-Language Models Using Knowledge Distillation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a pipeline that utilizes English-only vision-language models to train a monolingual model for a target language. |
Kshitij Gupta; Devansh Gautam; Radhika Mamidi; | arxiv-cs.CL | 2022-06-07 |
| 30 | Query and Attention Augmentation for Knowledge-Based Explainable Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge this research gap, we present Query and Attention Augmentation, a general approach that augments neural module networks to jointly reason about visual and external knowledge. |
Yifeng Zhang; Ming Jiang; Qi Zhao; | cvpr | 2022-06-07 |
| 31 | Transform-Retrieve-Generate: Natural Language-Centric Outside-Knowledge Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we call for an alternative paradigm for the OK-VQA task, which transforms the image into plain text, so that we can enable knowledge passage retrieval, and generative question-answering in the natural language space. |
FENG GAO et. al. | cvpr | 2022-06-07 |
| 32 | Revisiting The "Video" in Video-Language Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the atemporal probe (ATP), a new model for video-language analysis which provides a stronger bound on the baseline accuracy of multimodal models constrained by image-level understanding. |
SHYAMAL BUCH et. al. | cvpr | 2022-06-07 |
| 33 | Measuring Compositional Consistency for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop a question decomposition engine that programmatically deconstructs a compositional question into a directed acyclic graph of sub-questions. |
MONA GANDHI et. al. | cvpr | 2022-06-07 |
| 34 | ScanQA: 3D Question Answering for Spatial Scene Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a baseline model for 3D-QA, named ScanQA model, where the model learns a fused descriptor from 3D object proposals and encoded sentence embeddings. |
Daichi Azuma; Taiki Miyanishi; Shuhei Kurita; Motoaki Kawanabe; | cvpr | 2022-06-07 |
| 35 | SwapMix: Diagnosing and Regularizing The Over-Reliance on Visual Context in Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the robustness of VQA models from a novel perspective: visual context. |
VIPUL GUPTA et. al. | cvpr | 2022-06-07 |
| 36 | Episodic Memory Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Towards that end, we introduce (1) a new task — Episodic Memory Question Answering (EMQA) wherein an egocentric AI assistant is provided with a video sequence (the tour) and a question as an input and is asked to localize its answer to the question within the tour, (2) a dataset of grounded questions designed to probe the agent’s spatio-temporal understanding of the tour, and (3) a model for the task that encodes the scene as an allocentric, top-down semantic feature map and grounds the question into the map to localize the answer. |
SAMYAK DATTA et. al. | cvpr | 2022-06-07 |
| 37 | Invariant Grounding for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we first take a causal look at VideoQA and argue that invariant grounding is the key to ruling out the spurious correlations. Towards this end, we propose a new learning framework, Invariant Grounding for VideoQA (IGV), to ground the question-critical scene, whose causal relations with answers are invariant across different interventions on the complement. |
Yicong Li; Xiang Wang; Junbin Xiao; Wei Ji; Tat-Seng Chua; | cvpr | 2022-06-07 |
| 38 | MuKEA: Multimodal Knowledge Extraction and Accumulation for Knowledge-Based Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose MuKEA to represent multimodal knowledge by an explicit triplet to correlate visual objects and fact answers with implicit relations. |
YANG DING et. al. | cvpr | 2022-06-07 |
| 39 | Learning To Answer Questions in Dynamic Audio-Visual Scenarios Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the Audio-Visual Question Answering (AVQA) task, which aims to answer questions regarding different visual objects, sounds, and their associations in videos. |
GUANGYAO LI et. al. | cvpr | 2022-06-07 |
| 40 | V-Doc: Visual Questions Answers With Documents Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose V-Doc, a question-answering tool using document images and PDF, mainly for researchers and general non-deep learning experts looking to generate, process, and understand the document visual question answering tasks. |
YIHAO DING et. al. | cvpr | 2022-06-07 |
| 41 | Maintaining Reasoning Consistency in Compositional Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a dialog-like reasoning method for maintaining reasoning consistency in answering a compositional question and its sub-questions. |
Chenchen Jing; Yunde Jia; Yuwei Wu; Xinyu Liu; Qi Wu; | cvpr | 2022-06-07 |
| 42 | Grounding Answers for Visual Questions Asked By Visually Impaired People Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the VizWiz-VQA-Grounding dataset, the first dataset that visually grounds answers to visual questions asked by people with visual impairments. |
Chongyan Chen; Samreen Anjum; Danna Gurari; | cvpr | 2022-06-07 |
| 43 | WebQA: Multihop and Multimodal QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce WebQA, a challenging new benchmark that proves difficult for large-scale state-of-the-art models which lack language groundable visual representations for novel objects and the ability to reason, yet trivial for humans. |
YINGSHAN CHANG et. al. | cvpr | 2022-06-07 |
| 44 | On Efficient Approximate Queries Over Machine Learning Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a novel unified framework for approximate query answering by leveraging a proxy to minimize the oracle usage of finding high quality answers for both Precision-Target (PT) and Recall-Target (RT) queries. |
Dujian Ding; Sihem Amer-Yahia; Laks VS Lakshmanan; | arxiv-cs.DB | 2022-06-06 |
| 45 | Learning to Ask Like A Physician Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Discharge Summary Clinical Questions (DiSCQ), a newly curated question dataset composed of 2,000+ questions paired with the snippets of text (triggers) that prompted each question. |
ERIC LEHMAN et. al. | arxiv-cs.CL | 2022-06-06 |
| 46 | Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a framework to enhance the Dual-Encoders model with question answer cross-embeddings and a novel Geometry Alignment Mechanism (GAM) to align the geometry of embeddings from Dual-Encoders with that from Cross-Encoders. |
YANMENG WANG et. al. | arxiv-cs.CL | 2022-06-06 |
| 47 | Investigating The Use of Paraphrase Generation for Question Reformulation in The FRANK QA System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a study into the ability of paraphrase generation methods to increase the variety of natural language questions that the FRANK Question Answering system can answer. |
Nick Ferguson; Liane Guillou; Kwabena Nuamah; Alan Bundy; | arxiv-cs.CL | 2022-06-06 |
| 48 | From Pixels to Objects: Cubic Visual Attention for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Cubic Visual Attention (CVA) model by successfully applying a novel channel and spatial attention on object regions to improve VQA task. |
Jingkuan Song; Pengpeng Zeng; Lianli Gao; Heng Tao Shen; | arxiv-cs.CV | 2022-06-04 |
| 49 | QAGCN: A Graph Convolutional Network-based Multi-Relation Question Answering System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose QAGCN – a simple but effective and novel model that leverages attentional graph convolutional networks that can perform multi-step reasoning during the encoding of knowledge graphs. |
Ruijie Wang; Luca Rossetto; Michael Cochez; Abraham Bernstein; | arxiv-cs.AI | 2022-06-03 |
| 50 | A-OKVQA: A Benchmark for Visual Question Answering Using World Knowledge Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce A-OKVQA, a crowdsourced dataset composed of a diverse set of about 25K questions requiring a broad base of commonsense and world knowledge to answer. |
Dustin Schwenk; Apoorv Khandelwal; Christopher Clark; Kenneth Marino; Roozbeh Mottaghi; | arxiv-cs.CV | 2022-06-03 |
| 51 | Revisiting The Video in Video-Language Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the atemporal probe (ATP), a new model for video-language analysis which provides a stronger bound on the baseline accuracy of multimodal models constrained by image-level understanding. |
SHYAMAL BUCH et. al. | arxiv-cs.CV | 2022-06-03 |
| 52 | TCE at Qur’an QA 2022: Arabic Language Question Answering Over Holy Qur’an Using A Post-Processed Ensemble of BERT-based Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we describe our attempts at OSACT5 Qur’an QA 2022 Shared Task, which is a question answering challenge on the Holy Qur’an in Arabic. |
Mohammed ElKomy; Amany M. Sarhan; | arxiv-cs.CL | 2022-06-03 |
| 53 | VL-BEiT: Generative Vision-Language Pretraining Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a vision-language foundation model called VL-BEiT, which is a bidirectional multimodal Transformer learned by generative pretraining. |
Hangbo Bao; Wenhui Wang; Li Dong; Furu Wei; | arxiv-cs.CV | 2022-06-02 |
| 54 | MultiHiertt: Numerical Reasoning Over Multi Hierarchical Tabular and Textual Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To facilitate data analytical progress, we construct a new large-scale benchmark, MultiHiertt, with QA pairs over Multi Hierarchical Tabular and Textual data. |
Yilun Zhao; Yunxiang Li; Chenying Li; Rui Zhang; | arxiv-cs.AI | 2022-06-02 |
| 55 | Structured Two-stream Attention Network for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we specifically tackle the problem of video QA by proposing a Structured Two-stream Attention network, namely STA, to answer a free-form or open-ended natural language question about the content of a given video. |
LIANLI GAO et. al. | arxiv-cs.CV | 2022-06-02 |
| 56 | REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Specifically, we observe that in most state-of-the-art knowledge-based VQA methods: 1) visual features are extracted either from the whole image or in a sliding window manner for retrieving knowledge, and the important relationship within/among object regions is neglected; 2) visual features are not well utilized in the final answering model, which is counter-intuitive to some extent. Based on these observations, we propose a new knowledge-based VQA method REVIVE, which tries to utilize the explicit information of object regions not only in the knowledge retrieval stage but also in the answering model. |
YUANZE LIN et. al. | arxiv-cs.CV | 2022-06-02 |
| 57 | Knowledge Graph – Deep Learning: A Case Study in Question Answering in Aviation Safety Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Knowledge Graph (KG) guided Deep Learning (DL) based Question Answering (QA) system for aviation safety. |
ANKUSH AGARWAL et. al. | arxiv-cs.CL | 2022-05-31 |
| 58 | ZusammenQA: Data Augmentation with Specialized Models for Cross-lingual Open-retrieval Question Answering System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces our proposed system for the MIA Shared Task on Cross-lingual Open-retrieval Question Answering (COQA). |
CHIA-CHIEN HUNG et. al. | arxiv-cs.CL | 2022-05-30 |
| 59 | EA$^2$E: Improving Consistency with Event Awareness for Document-Level Argument Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we formulate event argument consistency as the constraints from event-event relations under the document-level setting. |
Qi Zeng; Qiusi Zhan; Heng Ji; | arxiv-cs.CL | 2022-05-30 |
| 60 | Visual Superordinate Abstraction for Robust Concept Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a visual superordinate abstraction framework for explicitly modeling semantic-aware visual subspaces (i.e. visual superordinates). |
Qi Zheng; Chaoyue Wang; Dadong Wang; Dacheng Tao; | arxiv-cs.CV | 2022-05-28 |
| 61 | V-Doc : Visual Questions Answers with Documents Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose V-Doc, a question-answering tool using document images and PDF, mainly for researchers and general non-deep learning experts looking to generate, process, and understand the document visual question answering tasks. |
YIHAO DING et. al. | arxiv-cs.AI | 2022-05-26 |
| 62 | Teaching Broad Reasoning Skills Via Decomposition-Guided Contexts Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This results in a pretraining dataset, named TeaBReaC, containing 525K multihop questions (with associated formal programs) covering about 900 reasoning patterns. We show that pretraining standard language models (LMs) on TeaBReaC before fine-tuning them on target datasets improves their performance by up to 13 EM points across 3 multihop QA datasets, with a 30 point gain on more complex questions. |
Harsh Trivedi; Niranjan Balasubramanian; Tushar Khot; Ashish Sabharwal; | arxiv-cs.CL | 2022-05-25 |
| 63 | QAMPARI: : An Open-domain Question Answering Benchmark for Questions with Many Answers from Multiple Paragraphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce QAMPARI, an ODQA benchmark, where question answers are lists of entities, spread across many paragraphs. |
SAMUEL JOSEPH AMOUYAL et. al. | arxiv-cs.CL | 2022-05-25 |
| 64 | LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our approach relies on LargE models with Prompt-Utilizing reranking Strategy (LEPUS): we construct an instruction-like prompt based on a candidate document path and compute a relevance score of the path as the probability of generating a given question, according to a pre-trained language model. |
Muhammad Khalifa; Lajanugen Logeswaran; Moontae Lee; Honglak Lee; Lu Wang; | arxiv-cs.CL | 2022-05-25 |
| 65 | Would You Ask It That Way? Measuring and Improving Question Naturalness for Knowledge Graph Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, the resulting datasets often fall short of representing genuinely natural and fluent language. In the present work, we investigate ways to characterize and remedy these shortcomings. |
Trond Linjordet; Krisztian Balog; | arxiv-cs.IR | 2022-05-25 |
| 66 | Intermediate Training on Question Answering Datasets Improves Generative Data Augmentation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Through thorough analyses, we observe that QA datasets that requires high-level reasoning abilities (e.g., abstractive and common-sense QA datasets) tend to give the best boost in performance in both few-shot and zero-shot settings. |
Dheeraj Mekala; Tu Vu; Jingbo Shang; | arxiv-cs.CL | 2022-05-25 |
| 67 | Reasoning Over Logically Interacted Conditions for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study a more challenging task where answers are constrained by a list of conditions that logically interact, which requires performing logical reasoning over the conditions to determine the correctness of the answers. |
Haitian Sun; William W. Cohen; Ruslan Salakhutdinov; | arxiv-cs.CL | 2022-05-25 |
| 68 | The Dialog Must Go On: Improving Visual Dialog Via Generative Self-Training Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a semi-supervised learning approach for visually-grounded dialog, called Generative Self-Training (GST), to leverage unlabeled images on the Web. |
Gi-Cheon Kang; Sungdong Kim; Jin-Hwa Kim; Donghyun Kwak; Byoung-Tak Zhang; | arxiv-cs.CV | 2022-05-25 |
| 69 | TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions Over Tabular Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, auto-regressive PLMs are challenged by recent emerging numerical reasoning datasets, such as TAT-QA, due to the error-prone implicit calculation. In this paper, we present TaCube, to pre-compute aggregation/arithmetic results for the table in advance, so that they are handy and readily available for PLMs to answer numerical reasoning questions. |
FAN ZHOU et. al. | arxiv-cs.IR | 2022-05-25 |
| 70 | Asking The Right Questions in Low Resource Template Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We compare questions to other ways of phrasing natural language prompts for TE. We propose a novel model to perform TE with prompts, and find it benefits from questions over other styles of prompts, and that they do not require an NLP background to author. |
Nils Holzenberger; Yunmo Chen; Benjamin Van Durme; | arxiv-cs.CL | 2022-05-25 |
| 71 | Investigating Information Inconsistency in Multilingual Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We analyze if different retriever models present different passages given the same question in different languages on TyDi QA and XOR-TyDi QA, two multilingualQA datasets. |
Shramay Palta; Haozhe An; Yifan Yang; Shuaiyi Huang; Maharshi Gor; | arxiv-cs.CL | 2022-05-24 |
| 72 | Rethinking Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Vision-and-language (V&L) models pretrained on large-scale multimodal data have demonstrated strong performance on various tasks such as image captioning and visual question answering (VQA). |
AISHWARYA AGRAWAL et. al. | arxiv-cs.CL | 2022-05-24 |
| 73 | Community Question Answering Entity Linking Via Leveraging Auxiliary Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we define a new task of CQA entity linking (CQAEL) as linking the textual entity mentions detected from CQA texts with their corresponding entities in a knowledge base. |
Yuhan Li; Wei Shen; Jianbo Gao; Yadong Wang; | arxiv-cs.CL | 2022-05-24 |
| 74 | Prompt Tuning for Discriminative Pre-trained Language Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present DPT, the first prompt tuning framework for discriminative PLMs, which reformulates NLP tasks into a discriminative language modeling problem. |
YUAN YAO et. al. | arxiv-cs.CL | 2022-05-23 |
| 75 | A Survey on Neural Open Information Extraction: Current Status and Future Directions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we provide an extensive overview of the-state-of-the-art neural OpenIE models, their key design decisions, strengths and weakness. |
SHAOWEN ZHOU et. al. | arxiv-cs.CL | 2022-05-23 |
| 76 | From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Existing works tend to utilize graph-based reasoning and question decomposition to obtain the reasoning chain, which inevitably introduces additional complexity and cumulative error to the system. To address the above issue, we propose a simple yet effective novel framework, From Easy to Hard (FE2H), to remove distracting information and obtain better contextual representations for the multi-hop QA task. |
Xin-Yi Li; Wei-Jun Lei; Yu-Bin Yang; | arxiv-cs.CL | 2022-05-23 |
| 77 | StreamingQA: A Benchmark for Adaptation to New Knowledge Over Time in Question Answering Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To study how semi-parametric QA models and their underlying parametric language models (LMs) adapt to evolving knowledge, we construct a new large-scale dataset, StreamingQA, with human written and generated questions asked on a given date, to be answered from 14 years of time-stamped news articles. |
ADAM LIŠKA et. al. | arxiv-cs.CL | 2022-05-23 |
| 78 | VQA-GNN: Reasoning with Multimodal Semantic Graph for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel visual question answering method, VQA-GNN, which unifies the image-level information and conceptual knowledge to perform joint reasoning of the scene. |
Yanan Wang; Michihiro Yasunaga; Hongyu Ren; Shinya Wada; Jure Leskovec; | arxiv-cs.CV | 2022-05-23 |
| 79 | On Measuring Social Biases in Prompt-Based Multi-Task Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study T0, a large-scale multi-task text-to-text language model trained using prompt-based learning. |
AFRA FEYZA AKYÜREK et. al. | arxiv-cs.CL | 2022-05-23 |
| 80 | QASem Parsing: Text-to-text Modeling of QA-based Semantics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Several recent works have suggested to represent semantic relations with questions and answers, decomposing textual information into separate interrogative natural language statements. In this paper, we consider three QA-based semantic tasks – namely, QA-SRL, QANom and QADiscourse, each targeting a certain type of predication – and propose to regard them as jointly providing a comprehensive representation of textual information. |
AYAL KLEIN et. al. | arxiv-cs.CL | 2022-05-23 |
| 81 | Language Models with Image Descriptors Are Strong Few-Shot Video-Language Learners Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The goal of this work is to build flexible video-language models that can generalize to various video-to-text tasks from few examples, such as domain-specific captioning, question answering, and future event prediction. |
ZHENHAILONG WANG et. al. | arxiv-cs.CV | 2022-05-22 |
| 82 | NS3: Neuro-Symbolic Semantic Code Search Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, current language models are known to struggle with longer, compositional text, and multi-step reasoning. To overcome this limitation, we propose supplementing the query sentence with a layout of its semantic structure. |
SHUSHAN ARAKELYAN et. al. | arxiv-cs.LG | 2022-05-21 |
| 83 | Interpretable Proof Generation Via Iterative Backward Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present IBR, an Iterative Backward Reasoning model to solve the proof generation tasks on rule-based Question Answering (QA), where models are required to reason over a series of textual rules and facts to find out the related proof path and derive the final answer. |
Hanhao Qu; Yu Cao; Jun Gao; Liang Ding; Ruifeng Xu; | arxiv-cs.CL | 2022-05-21 |
| 84 | Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose three novel sentence-level transformer pre-training objectives that incorporate paragraph-level semantics within and across documents, to improve the performance of transformers for AS2, and mitigate the requirement of large labeled datasets. |
Luca Di Liello; Siddhant Garg; Luca Soldaini; Alessandro Moschitti; | arxiv-cs.CL | 2022-05-20 |
| 85 | Down and Across: Introducing Crossword-Solving As A New NLP Benchmark Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce solving crossword puzzles as a new natural language understanding task. |
Saurabh Kulshreshtha; Olga Kovaleva; Namrata Shivagunde; Anna Rumshisky; | arxiv-cs.CL | 2022-05-20 |
| 86 | Automated Crossword Solving Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present the Berkeley Crossword Solver, a state-of-the-art approach for automatically solving crossword puzzles. |
ERIC WALLACE et. al. | arxiv-cs.CL | 2022-05-19 |
| 87 | Two-Step Question Retrieval for Open-Domain QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a two-step question retrieval model, SQuID (Sequential Question-Indexed Dense retrieval) and distant supervision for training. |
YEON SEONWOO et. al. | arxiv-cs.CL | 2022-05-19 |
| 88 | ERNIE-Search: Bridging Cross-Encoder with Dual-Encoder Via Self On-the-fly Distillation for Dense Passage Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel distillation method that significantly advances cross-architecture distillation for dual-encoders. |
YUXIANG LU et. al. | arxiv-cs.CL | 2022-05-18 |
| 89 | Evaluation of Transfer Learning for Polish with A Text-to-Text Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details 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 |
| 90 | Modeling Exemplification in Long-form Question Answering Via Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we provide the first computational study of exemplification in QA, performing a fine-grained annotation of different types of examples (e.g., hypotheticals, anecdotes) in three corpora. |
Shufan Wang; Fangyuan Xu; Laure Thompson; Eunsol Choi; Mohit Iyyer; | arxiv-cs.CL | 2022-05-18 |
| 91 | Entailment Tree Explanations Via Iterative Retrieval-Generation Reasoner Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Structured explanations, called entailment trees, were recently suggested as a way to explain and inspect a QA system’s answer. In order to better generate such entailment trees, we propose an architecture called Iterative Retrieval-Generation Reasoner (IRGR). |
DANILO RIBEIRO et. al. | arxiv-cs.CL | 2022-05-18 |
| 92 | Modeling Multi-hop Question Answering As Single Sequence Prediction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a simple generative approach (PathFid) that extends the task beyond just answer generation by explicitly modeling the reasoning process to resolve the answer for multi-hop questions. |
Semih Yavuz; Kazuma Hashimoto; Yingbo Zhou; Nitish Shirish Keskar; Caiming Xiong; | arxiv-cs.CL | 2022-05-18 |
| 93 | CLIP Models Are Few-Shot Learners: Empirical Studies on VQA and Visual Entailment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we empirically show that CLIP can be a strong vision-language few-shot learner by leveraging the power of language. |
Haoyu Song; Li Dong; Weinan Zhang; Ting Liu; Furu Wei; | acl | 2022-05-17 |
| 94 | FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we find that the spreadsheet formula, a commonly used language to perform computations on numerical values in spreadsheets, is a valuable supervision for numerical reasoning in tables. |
ZHOUJUN CHENG et. al. | acl | 2022-05-17 |
| 95 | Simple and Effective Knowledge-Driven Query Expansion for QA-Based Product Attribute Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We thus propose simple knowledge-driven query expansion based on possible answers (values) of a query (attribute) for QA-based AVE. |
Keiji Shinzato; Naoki Yoshinaga; Yandi Xia; Wei-Te Chen; | acl | 2022-05-17 |
| 96 | Answer-level Calibration for Free-form Multiple Choice Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we consider the question answering format, where we need to choose from a set of (free-form) textual choices of unspecified lengths given a context. |
Sawan Kumar; | acl | 2022-05-17 |
| 97 | Subgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a trainable subgraph retriever (SR) decoupled from the subsequent reasoning process, which enables a plug-and-play framework to enhance any subgraph-oriented KBQA model. |
JING ZHANG et. al. | acl | 2022-05-17 |
| 98 | Ditch The Gold Standard: Re-evaluating Conversational Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we conduct the first large-scale human evaluation of state-of-the-art conversational QA systems, where human evaluators converse with models and judge the correctness of their answers. |
Huihan Li; Tianyu Gao; Manan Goenka; Danqi Chen; | acl | 2022-05-17 |
| 99 | QAConv: Question Answering on Informative Conversations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces QAConv, a new question answering (QA) dataset that uses conversations as a knowledge source. |
Chien-Sheng Wu; Andrea Madotto; Wenhao Liu; Pascale Fung; Caiming Xiong; | acl | 2022-05-17 |
| 100 | Hyperlink-induced Pre-training for Passage Retrieval in Open-domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, there still remains a large discrepancy between the provided upstream signals and the downstream question-passage relevance, which leads to less improvement. To bridge this gap, we propose the HyperLink-induced Pre-training (HLP), a method to pre-train the dense retriever with the text relevance induced by hyperlink-based topology within Web documents. |
JIAWEI ZHOU et. al. | acl | 2022-05-17 |
| 101 | HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a new dataset, HiTab, to study question answering (QA) and natural language generation (NLG) over hierarchical tables. |
ZHOUJUN CHENG et. al. | acl | 2022-05-17 |
| 102 | Hypergraph Transformer: Weakly-Supervised Multi-hop Reasoning for Knowledge-based Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Answering complex questions that require multi-hop reasoning under weak supervision is considered as a challenging problem since i) no supervision is given to the reasoning process and ii) high-order semantics of multi-hop knowledge facts need to be captured. In this paper, we introduce a concept of hypergraph to encode high-level semantics of a question and a knowledge base, and to learn high-order associations between them. |
Yu-Jung Heo; Eun-Sol Kim; Woo Suk Choi; Byoung-Tak Zhang; | acl | 2022-05-17 |
| 103 | On The Robustness of Question Rewriting Systems to Questions of Varying Hardness Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we are interested in the robustness of a QR system to questions varying in rewriting hardness or difficulty. |
Hai Ye; Hwee Tou Ng; Wenjuan Han; | acl | 2022-05-17 |
| 104 | Sequence-to-Sequence Knowledge Graph Completion and Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We show that an off-the-shelf encoder-decoder Transformer model can serve as a scalable and versatile KGE model obtaining state-of-the-art results for KG link prediction and incomplete KG question answering. |
Apoorv Saxena; Adrian Kochsiek; Rainer Gemulla; | acl | 2022-05-17 |
| 105 | Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Drawing on the reading education research, we introduce FairytaleQA, a dataset focusing on narrative comprehension of kindergarten to eighth-grade students. |
YING XU et. al. | acl | 2022-05-17 |
| 106 | Predicting Difficulty and Discrimination of Natural Language Questions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: More recently, IRT has been used to similarly characterize item difficulty and discrimination for natural language models across various datasets (Lalor et al., 2019; Vania et al., 2021; Rodriguez et al., 2021). In this work, we explore predictive models for directly estimating and explaining these traits for natural language questions in a question-answering context. |
Matthew Byrd; Shashank Srivastava; | acl | 2022-05-17 |
| 107 | Open Domain Question Answering with A Unified Knowledge Interface Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: While data-to-text generation has the potential to serve as a universal interface for data and text, its feasibility for downstream tasks remains largely unknown. In this work, we bridge this gap and use the data-to-text method as a means for encoding structured knowledge for open-domain question answering. |
Kaixin Ma; Hao Cheng; Xiaodong Liu; Eric Nyberg; Jianfeng Gao; | acl | 2022-05-17 |
| 108 | It Is AI’s Turn to Ask Humans A Question: Question-Answer Pair Generation for Children’s Story Books Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We design an automated question-answer generation (QAG) system for this education scenario: given a story book at the kindergarten to eighth-grade level as input, our system can automatically generate QA pairs that are capable of testing a variety of dimensions of a student’s comprehension skills. |
BINGSHENG YAO et. al. | acl | 2022-05-17 |
| 109 | Simulating Bandit Learning from User Feedback for Extractive Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study learning from user feedback for extractive question answering by simulating feedback using supervised data. |
Ge Gao; Eunsol Choi; Yoav Artzi; | acl | 2022-05-17 |
| 110 | A Copy-Augmented Generative Model for Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we focus on improving the effectiveness of the reader module and propose a novel copy-augmented generative approach that integrates the merits of both extractive and generative readers. |
Shuang Liu; Dong Wang; Xiaoguang Li; Minghui Huang; Meizhen Ding; | acl | 2022-05-17 |
| 111 | ConditionalQA: A Complex Reading Comprehension Dataset with Conditional Answers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe a Question Answering (QA) dataset that contains complex questions with conditional answers, i.e. the answers are only applicable when certain conditions apply. |
Haitian Sun; William Cohen; Ruslan Salakhutdinov; | acl | 2022-05-17 |
| 112 | Gender and Racial Bias in Visual Question Answering Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We conclude the paper by proposing solutions to alleviate the problem before, during, and after the dataset collection process. |
Yusuke Hirota; Yuta Nakashima; Noa Garcia; | arxiv-cs.CV | 2022-05-17 |
| 113 | KaFSP: Knowledge-Aware Fuzzy Semantic Parsing for Conversational Question Answering Over A Large-Scale Knowledge Base Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study two issues of semantic parsing approaches to conversational question answering over a large-scale knowledge base: (1) The actions defined in grammar are not sufficient to handle uncertain reasoning common in real-world scenarios. |
Junzhuo Li; Deyi Xiong; | acl | 2022-05-17 |
| 114 | C-MORE: Pretraining to Answer Open-Domain Questions By Consulting Millions of References Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we automatically construct a large-scale corpus that meets all three criteria by consulting millions of references cited within Wikipedia. |
XIANG YUE et. al. | acl | 2022-05-17 |
| 115 | Training Data Is More Valuable Than You Think: A Simple and Effective Method By Retrieving from Training Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Surprisingly, we found that REtrieving from the traINing datA (REINA) only can lead to significant gains on multiple NLG and NLU tasks. |
SHUOHANG WANG et. al. | acl | 2022-05-17 |
| 116 | RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present RnG-KBQA, a Rank-and-Generate approach for KBQA, which remedies the coverage issue with a generation model while preserving a strong generalization capability. |
Xi Ye; Semih Yavuz; Kazuma Hashimoto; Yingbo Zhou; Caiming Xiong; | acl | 2022-05-17 |
| 117 | Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we devise a Learning to Imagine (L2I) module, which can be seamlessly incorporated into NDR models to perform the imagination of unseen counterfactual. |
MOXIN LI et. al. | acl | 2022-05-17 |
| 118 | Improving Time Sensitivity for Question Answering Over Temporal Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a time-sensitive question answering (TSQA) framework to tackle these problems. |
Chao Shang; Guangtao Wang; Peng Qi; Jing Huang; | acl | 2022-05-17 |
| 119 | MMCoQA: Conversational Question Answering Over Text, Tables, and Images Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we hence define a novel research task, i.e., multimodal conversational question answering (MMCoQA), aiming to answer users’ questions with multimodal knowledge sources via multi-turn conversations. |
Yongqi Li; Wenjie Li; Liqiang Nie; | acl | 2022-05-17 |
| 120 | Unsupervised Multiple-choice Question Generation for Out-of-domain Q&A Fine-tuning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose an approach for generating a fine-tuning dataset thanks to a rule-based algorithm that generates questions and answers from unannotated sentences. |
Guillaume Le Berre; Christophe Cerisara; Philippe Langlais; Guy Lapalme; | acl | 2022-05-17 |
| 121 | Retrieval-guided Counterfactual Generation for QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We focus on the task of creating counterfactuals for question answering, which presents unique challenges related to world knowledge, semantic diversity, and answerability. To address these challenges, we develop a Retrieve-Generate-Filter(RGF) technique to create counterfactual evaluation and training data with minimal human supervision. |
Bhargavi Paranjape; Matthew Lamm; Ian Tenney; | acl | 2022-05-17 |
| 122 | Synthetic Question Value Estimation for Domain Adaptation of Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel idea of training a question value estimator (QVE) that directly estimates the usefulness of synthetic questions for improving the target-domain QA performance. |
Xiang Yue; Ziyu Yao; Huan Sun; | acl | 2022-05-17 |
| 123 | Educational Question Generation of Children Storybooks Via Question Type Distribution Learning and Event-centric Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel question generation method that first learns the question type distribution of an input story paragraph, and then summarizes salient events which can be used to generate high-cognitive-demand questions. |
ZHENJIE ZHAO et. al. | acl | 2022-05-17 |
| 124 | Clickbait Spoiling Via Question Answering and Passage Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce and study the task of clickbait spoiling: generating a short text that satisfies the curiosity induced by a clickbait post. |
Matthias Hagen; Maik Fr�be; Artur Jurk; Martin Potthast; | acl | 2022-05-17 |
| 125 | Miutsu: NTU’s TaskBot for The Alexa Prize Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces Miutsu, National Taiwan University’s Alexa Prize TaskBot, which is designed to assist users in completing tasks requiring multiple steps and decisions in two different domains — home improvement and cooking. |
YEN-TING LIN et. al. | arxiv-cs.CL | 2022-05-16 |
| 126 | A Neuro-Symbolic ASP Pipeline for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a neuro-symbolic visual question answering (VQA) pipeline for CLEVR, which is a well-known dataset that consists of pictures showing scenes with objects and questions related to them. |
Thomas Eiter; Nelson Higuera; Johannes Oetsch; Michael Pritz; | arxiv-cs.AI | 2022-05-16 |
| 127 | Heroes, Villains, and Victims, and GPT-3: Automated Extraction of Character Roles Without Training Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper shows how to use large-scale pre-trained language models to extract character roles from narrative texts without training data. |
Dominik Stammbach; Maria Antoniak; Elliott Ash; | arxiv-cs.CL | 2022-05-16 |
| 128 | Harnessing Multilingual Resources to Question Answering in Arabic Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The goal of the paper is to predict answers to questions given a passage of Qur’an. |
Khalid Alnajjar; Mika Hämäläinen; | arxiv-cs.CL | 2022-05-16 |
| 129 | Not to Overfit or Underfit? A Study of Domain Generalization in Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here we examine the contrasting view that multi-source domain generalization (DG) is in fact a problem of mitigating source domain underfitting: models not adequately learning the signal in their multi-domain training data. |
Md Arafat Sultan; Avirup Sil; Radu Florian; | arxiv-cs.CL | 2022-05-15 |
| 130 | Knowledge Graph Question Answering Datasets and Their Generalizability: Are They Enough for Future Research? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a mitigation method for re-splitting available KGQA datasets to enable their applicability to evaluate generalization, without any cost and manual effort. |
Longquan Jiang; Ricardo Usbeck; | arxiv-cs.CL | 2022-05-13 |
| 131 | Near-Negative Distinction: Giving A Second Life to Human Evaluation Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new and simple automatic evaluation method for NLG called Near-Negative Distinction (NND) that repurposes prior human annotations into NND tests. |
Philippe Laban; Chien-Sheng Wu; Wenhao Liu; Caiming Xiong; | arxiv-cs.CL | 2022-05-13 |
| 132 | Modeling Semantic Composition with Syntactic Hypergraph for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, word representations are often not able to convey a complete description of textual concepts, which are in general described by the compositions of certain words. To address this issue, we propose to first build a syntactic dependency tree for each question with an off-the-shelf tool and use it to guide the extraction of meaningful word compositions. |
Zenan Xu; Wanjun Zhong; Qinliang Su; Zijing Ou; Fuwei Zhang; | arxiv-cs.CV | 2022-05-13 |
| 133 | AiSocrates: Towards Answering Ethical Quandary Questions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we challenge the capability of LLMs with the new task of Ethical Quandary Generative Question Answering. |
YEJIN BANG et. al. | arxiv-cs.CL | 2022-05-12 |
| 134 | Lifting The Curse of Multilinguality By Pre-training Modular Transformers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Multilingual pre-trained models are known to suffer from the curse of multilinguality, which causes per-language performance to drop as they cover more languages. We address this issue by introducing language-specific modules, which allows us to grow the total capacity of the model, while keeping the total number of trainable parameters per language constant. |
JONAS PFEIFFER et. al. | arxiv-cs.CL | 2022-05-12 |
| 135 | DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in A Low-resource Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes the DTW entry to the Quran QA 2022 shared task. |
Damith Premasiri; Tharindu Ranasinghe; Wajdi Zaghouani; Ruslan Mitkov; | arxiv-cs.CL | 2022-05-12 |
| 136 | Learning to Answer Visual Questions from Web Videos Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to avoid manual annotation and generate a large-scale training dataset for video question answering making use of automatic cross-modal supervision. |
Antoine Yang; Antoine Miech; Josef Sivic; Ivan Laptev; Cordelia Schmid; | arxiv-cs.CV | 2022-05-10 |
| 137 | ProQA: Structural Prompt-based Pre-training for Unified Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The specialty in QA research hinders systems from modeling commonalities between tasks and generalization for wider applications. To address this issue, we present ProQA, a unified QA paradigm that solves various tasks through a single model. |
WANJUN ZHONG et. al. | arxiv-cs.CL | 2022-05-09 |
| 138 | Joint Learning of Object Graph and Relation Graph for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel Dual Message-passing enhanced Graph Neural Network (DM-GNN), which can obtain a balanced representation by properly encoding multi-scale scene graph information. |
Hao Li; Xu Li; Belhal Karimi; Jie Chen; Mingming Sun; | arxiv-cs.CV | 2022-05-09 |
| 139 | Multilevel Hierarchical Network with Multiscale Sampling for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: While most existing approaches ignore the visual appearance-motion information at different temporal scales, it is unknown how to incorporate the multilevel processing capacity of a deep learning model with such multiscale information. Targeting these issues, this paper proposes a novel Multilevel Hierarchical Network (MHN) with multiscale sampling for VideoQA. |
Min Peng; Chongyang Wang; Yuan Gao; Yu Shi; Xiang-Dong Zhou; | arxiv-cs.CV | 2022-05-09 |
| 140 | Chart Question Answering: State of The Art and Future Directions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we systematically review the current state-of-the-art research focusing on the problem of chart question answering. |
Enamul Hoque; Parsa Kavehzadeh; Ahmed Masry; | arxiv-cs.CL | 2022-05-08 |
| 141 | Better Retrieval May Not Lead to Better Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: A popular approach to improve the system’s performance is to improve the quality of the retrieved context from the IR stage. In this work we show that for StrategyQA, a challenging open-domain QA dataset that requires multi-hop reasoning, this common approach is surprisingly ineffective — improving the quality of the retrieved context hardly improves the system’s performance. |
Zhengzhong Liang; Tushar Khot; Steven Bethard; Mihai Surdeanu; Ashish Sabharwal; | arxiv-cs.CL | 2022-05-07 |
| 142 | Number Entity Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Though numbers are typically not accounted for distinctly in most NLP tasks, there is still an underlying amount of numeracy already exhibited by NLP models. In this work, we attempt to tap this potential of state-of-the-art NLP models and transfer their ability to boost performance in related tasks. |
Dhanasekar Sundararaman; Vivek Subramanian; Guoyin Wang; Liyan Xu; Lawrence Carin; | arxiv-cs.CL | 2022-05-07 |
| 143 | QLEVR: A Diagnostic Dataset for Quantificational Language and Elementary Visual Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a minimally biased, diagnostic visual question-answering dataset, QLEVR, that goes beyond existential and numerical quantification and focus on more complex quantifiers and their combinations, e.g., asking whether there are more than two red balls that are smaller than at least three blue balls in an image. |
Zechen Li; Anders Søgaard; | arxiv-cs.CV | 2022-05-06 |
| 144 | Translating Place-Related Questions to GeoSPARQL Queries Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Many place-related questions can only be answered by complex spatial reasoning, a task poorly supported by factoid question retrieval. Such reasoning using combinations of spatial … |
Ehsan Hamzei; Martin Tomko; Stephan Winter; | arxiv-cs.IR | 2022-05-06 |
| 145 | KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, most existing approaches for MRC may perform poorly in the few-shot learning scenario. To solve this issue, we propose a novel framework named Knowledge Enhanced Contrastive Prompt-tuning (KECP). |
JIANING WANG et. al. | arxiv-cs.CL | 2022-05-06 |
| 146 | From Easy to Hard: Learning Language-guided Curriculum for Visual Question Answering on Remote Sensing Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Directly training a model with questions in a random order may confuse the model and limit the performance. To address these two problems, in this paper, a multi-level visual feature learning method is proposed to jointly extract language-guided holistic and regional image features. |
Zhenghang Yuan; Lichao Mou; Qi Wang; Xiao Xiang Zhu; | arxiv-cs.CV | 2022-05-06 |
| 147 | What Is Right for Me Is Not Yet Right for You: A Dataset for Grounding Relative Directions Via Multi-Task Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the challenging problem of grounding relative directions with end-to-end neural networks. |
Jae Hee Lee; Matthias Kerzel; Kyra Ahrens; Cornelius Weber; Stefan Wermter; | arxiv-cs.CV | 2022-05-05 |
| 148 | Declaration-based Prompt Tuning for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate the problem, we propose an innovative VL fine-tuning paradigm (named Declaration-based Prompt Tuning, abbreviated as DPT), which jointly optimizes the objectives of pre-training and fine-tuning of VQA model, boosting the effective adaptation of pre-trained VL models to the downstream task. |
Yuhang Liu; Wei Wei; Daowan Peng; Feida Zhu; | arxiv-cs.CV | 2022-05-05 |
| 149 | METGEN: A Module-Based Entailment Tree Generation Framework for Answer Explanation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose METGEN, a Module-based Entailment Tree GENeration framework that has multiple modules and a reasoning controller. |
Ruixin Hong; Hongming Zhang; Xintong Yu; Changshui Zhang; | arxiv-cs.CL | 2022-05-05 |
| 150 | KenSwQuAD — A Question Answering Dataset for Swahili Low Resource Language Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This research developed a Kencorpus Swahili Question Answering Dataset KenSwQuAD from raw data of Swahili language, which is a low resource language predominantly spoken in Eastern African and also has speakers in other parts of the world. |
BARACK WANJAWA et. al. | arxiv-cs.CL | 2022-05-04 |
| 151 | Compositional Task-Oriented Parsing As Abstractive Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we continue to explore naturalized semantic parsing by presenting a general reduction of TOP to abstractive question answering that overcomes some limitations of canonical paraphrasing. |
Wenting Zhao; Konstantine Arkoudas; Weiqi Sun; Claire Cardie; | arxiv-cs.CL | 2022-05-04 |
| 152 | All You May Need for VQA Are Image Captions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a method that automatically derives VQA examples at volume, by leveraging the abundance of existing image-caption annotations combined with neural models for textual question generation. |
SORAVIT CHANGPINYO et. al. | arxiv-cs.CV | 2022-05-04 |
| 153 | Analysing The Robustness of Dual Encoders for Dense Retrieval Against Misspellings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study the robustness of dense retrievers against typos in the user question. |
Georgios Sidiropoulos; Evangelos Kanoulas; | arxiv-cs.IR | 2022-05-04 |
| 154 | XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose XLTime, a novel framework for multilingual TEE. |
YUWEI CAO et. al. | arxiv-cs.CL | 2022-05-03 |
| 155 | DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queries Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is to provide a benchmark dataset for multi-modal QA systems, and to open up new avenues of research in improving question answering over EHR structured data by using context from unstructured clinical data. |
Jayetri Bardhan; Anthony Colas; Kirk Roberts; Daisy Zhe Wang; | arxiv-cs.AI | 2022-05-02 |
| 156 | Answer-Me: Multi-Task Open-Vocabulary Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Answer-Me, a task-aware multi-task framework which unifies a variety of question answering tasks, such as, visual question answering, visual entailment, visual reasoning. |
AJ PIERGIOVANNI et. al. | arxiv-cs.CV | 2022-05-02 |
| 157 | Re-defining Radiology Quality Assurance (QA) — Artificial Intelligence (AI)-Based QA By Restricted Investigation of Unequal Scores (AQUARIUS) Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we present a novel approach, Artificial Intelligence (AI)-Based QUality Assurance by Restricted Investigation of Unequal Scores (AQUARIUS), for re-defining radiology QA, which reduces human effort by up to several orders of magnitude over existing approaches. |
Axel Wismueller; Larry Stockmaster; Ali Vosoughi; | arxiv-cs.HC | 2022-05-01 |
| 158 | ELQA: A Corpus of Questions and Answers About The English Language Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a community-sourced dataset for English Language Question Answering (ELQA), which consists of more than 180k questions and answers on numerous topics about English language such as grammar, meaning, fluency, and etymology. |
Shabnam Behzad; Keisuke Sakaguchi; Nathan Schneider; Amir Zeldes; | arxiv-cs.CL | 2022-05-01 |
| 159 | Clues Before Answers: Generation-Enhanced Multiple-Choice QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To exploit the generation capability and underlying knowledge of a pre-trained encoder-decoder model, in this paper, we propose a generation-enhanced MCQA model named GenMC. |
ZIXIAN HUANG et. al. | arxiv-cs.CL | 2022-04-30 |
| 160 | Answer Consolidation: Formulation and Benchmarking Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we formulate the problem of answer consolidation, where answers are partitioned into multiple groups, each representing different aspects of the answer set. |
Wenxuan Zhou; Qiang Ning; Heba Elfardy; Kevin Small; Muhao Chen; | arxiv-cs.CL | 2022-04-29 |
| 161 | End-to-end Spoken Conversational Question Answering: Task, Dataset and Model Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this task, our main objective is to build the system to deal with conversational questions based on the audio recordings, and to explore the plausibility of providing more cues from different modalities with systems in information gathering. To this end, instead of directly adopting automatically generated speech transcripts with highly noisy data, we propose a novel unified data distillation approach, DDNet, which effectively ingests cross-modal information to achieve fine-grained representations of the speech and language modalities. |
CHENYU YOU et. al. | arxiv-cs.CL | 2022-04-29 |
| 162 | VICTOR: An Implicit Approach to Mitigate Misinformation Via Continuous Verification Reading Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We design and evaluate VICTOR, an easy-to-apply module on top of a recommender system to mitigate misinformation. |
Kuan-Chieh Lo; Shih-Chieh Dai; Aiping Xiong; Jing Jiang; Lun-Wei Ku; | www | 2022-04-29 |
| 163 | Flamingo: A Visual Language Model for Few-Shot Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Building models that can be rapidly adapted to numerous tasks using only a handful of annotated examples is an open challenge for multimodal machine learning research. We introduce Flamingo, a family of Visual Language Models (VLM) with this ability. |
JEAN-BAPTISTE ALAYRAC et. al. | arxiv-cs.CV | 2022-04-29 |
| 164 | Unified Question Generation with Continual Lifelong Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To solve the problems, we propose a model named Unified-QG based on lifelong learning techniques, which can continually learn QG tasks across different datasets and formats. |
WEI YUAN et. al. | www | 2022-04-29 |
| 165 | Can Machine Translation Be A Reasonable Alternative for Multilingual Question Answering Systems Over Knowledge Graphs? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we discuss Knowledge Graph Question Answering (KGQA) systems that aim at providing natural language access to data stored in Knowledge Graphs (KG). |
Aleksandr Perevalov; Andreas Both; Dennis Diefenbach; Axel-Cyrille Ngonga Ngomo; | www | 2022-04-29 |
| 166 | Towards A Multi-View Attentive Matching for Personalized Expert Finding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a personalized expert finding method with a multi-view attentive matching mechanism. |
QIYAO PENG et. al. | www | 2022-04-29 |
| 167 | Inferring Implicit Relations with Language Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate why current models struggle with implicit reasoning question answering (QA) tasks, by decoupling inference of reasoning steps from their execution. |
Uri Katz; Mor Geva; Jonathan Berant; | arxiv-cs.CL | 2022-04-28 |
| 168 | Reliable Visual Question Answering: Abstain Rather Than Answer Incorrectly Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we promote a problem formulation for reliable VQA, where we prefer abstention over providing an incorrect answer. |
SPENCER WHITEHEAD et. al. | arxiv-cs.CV | 2022-04-28 |
| 169 | Towards Teachable Reasoning Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is a teachable reasoning system for question-answering (QA), where a user can interact with faithful answer explanations, and correct errors so that the system improves over time. |
Bhavana Dalvi; Oyvind Tafjord; Peter Clark; | arxiv-cs.CL | 2022-04-27 |
| 170 | Plug-and-Play Adaptation for Continuously-updated QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Language models (LMs) have shown great potential as implicit knowledge bases (KBs). |
KYUNGJAE LEE et. al. | arxiv-cs.CL | 2022-04-27 |
| 171 | A Method of Query Graph Reranking for Knowledge Base Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a novel reranking method to better choose the optimal query graph, a sub-graph of knowledge graph, to retrieve the answer for an input question in Knowledge Base Question Answering (KBQA). |
Yonghui Jia; Wenliang Chen; | arxiv-cs.CL | 2022-04-27 |
| 172 | Better Query Graph Selection for Knowledge Base Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a novel approach based on semantic parsing to improve the performance of Knowledge Base Question Answering (KBQA). |
Yonghui Jia; Wenliang Chen; | arxiv-cs.CL | 2022-04-26 |
| 173 | Testing The Ability of Language Models to Interpret Figurative Language Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, figurative language has been a relatively under-studied area in NLP, and it remains an open question to what extent modern language models can interpret nonliteral phrases. To address this question, we introduce Fig-QA, a Winograd-style nonliteral language understanding task consisting of correctly interpreting paired figurative phrases with divergent meanings. |
Emmy Liu; Chen Cui; Kenneth Zheng; Graham Neubig; | arxiv-cs.CL | 2022-04-26 |
| 174 | Science Checker: Extractive-Boolean Question Answering For Scientific Fact Checking Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a multi-task approach for verifying the scientific questions based on a joint reasoning from facts and evidence in research articles. |
Loïc Rakotoson; Charles Letaillieur; Sylvain Massip; Fréjus Laleye; | arxiv-cs.CL | 2022-04-26 |
| 175 | Conversational Question Answering on Heterogeneous Sources Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper addresses the novel issue of jointly tapping into all of these together, this way boosting answer coverage and confidence. We present CONVINSE, an end-to-end pipeline for ConvQA over heterogeneous sources, operating in three stages: i) learning an explicit structured representation of an incoming question and its conversational context, ii) harnessing this frame-like representation to uniformly capture relevant evidences from KB, text, and tables, and iii) running a fusion-in-decoder model to generate the answer. |
Philipp Christmann; Rishiraj Saha Roy; Gerhard Weikum; | arxiv-cs.IR | 2022-04-25 |
| 176 | Rethinking Multi-Modal Alignment in Video Question Answering from Feature and Sample Perspectives Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we reconsider the multi-modal alignment problem in VideoQA from feature and sample perspectives to achieve better performance. |
SHAONING XIAO et. al. | arxiv-cs.CV | 2022-04-25 |
| 177 | MEKER: Memory Efficient Knowledge Embedding Representation for Link Prediction and Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a MEKER, a memory-efficient KG embedding model, which yields SOTA-comparable performance on link prediction tasks and KG-based Question Answering. |
Viktoriia Chekalina; Anton Razzhigaev; Albert Sayapin; Evgeny Frolov; Alexander Panchenko; | arxiv-cs.CL | 2022-04-22 |
| 178 | A Summary of The ALQAC 2021 Competition Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we summarize each team’s approaches, official results, and some discussion about the competition. |
NGUYEN HA THANH et. al. | arxiv-cs.CL | 2022-04-22 |
| 179 | Benchmarking Answer Verification Methods for Question Answering-Based Summarization Evaluation Metrics Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we benchmark the lexical answer verification methods which have been used by current QA-based metrics as well as two more sophisticated text comparison methods, BERTScore and LERC. |
Daniel Deutsch; Dan Roth; | arxiv-cs.CL | 2022-04-21 |
| 180 | LingYi: Medical Conversational Question Answering System Based on Multi-modal Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a medical conversational question answering (CQA) system based on the multi-modal knowledge graph, namely LingYi, which is designed as a pipeline framework to maintain high flexibility. |
FEI XIA et. al. | arxiv-cs.CL | 2022-04-20 |
| 181 | Synthetic Target Domain Supervision for Open Retrieval QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Neural passage retrieval is a new and promising approach in open retrieval question answering. In this work, we stress-test the Dense Passage Retriever (DPR) — a state-of-the-art (SOTA) open domain neural retrieval model — on closed and specialized target domains such as COVID-19, and find that it lags behind standard BM25 in this important real-world setting. |
REVANTH GANGI REDDY et. al. | arxiv-cs.CL | 2022-04-20 |
| 182 | Clotho-AQA: A Crowdsourced Dataset for Audio Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce Clotho-AQA, a dataset for Audio question answering consisting of 1991 audio files each between 15 to 30 seconds in duration selected from the Clotho dataset. |
Samuel Lipping; Parthasaarathy Sudarsanam; Konstantinos Drossos; Tuomas Virtanen; | arxiv-cs.SD | 2022-04-20 |
| 183 | Where Was COVID-19 First Discovered? Designing A Question-Answering System for Pandemic Situations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To carry out our research, we followed a design science research approach and applied Ingwersen’s cognitive model of information retrieval interaction to inform our design process from a socio-technical lens. |
Johannes Graf; Gino Lancho; Patrick Zschech; Kai Heinrich; | arxiv-cs.CL | 2022-04-19 |
| 184 | A Survey on Multi-hop Question Answering and Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work aims to provide a general and formal definition of MHQA task, and organize and summarize existing MHQA frameworks. |
Vaibhav Mavi; Anubhav Jangra; Adam Jatowt; | arxiv-cs.CL | 2022-04-19 |
| 185 | Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Even if we manage a small-scale one, a bottleneck that remains is that the labeled data are heavily imbalanced (only a few segments are relevant) –limiting the gain in this domain. Therefore, in this paper, we develop a novel data augmentation framework based on ensembling retriever models that captures the relevant text segments from unlabeled policy documents and expand the positive examples in the training set. |
Md Rizwan Parvez; Jianfeng Chi; Wasi Uddin Ahmad; Yuan Tian; Kai-Wei Chang; | arxiv-cs.CL | 2022-04-19 |
| 186 | CBR-iKB: A Case-Based Reasoning Approach for Question Answering Over Incomplete Knowledge Bases Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Yet, in many question answering applications coupled with knowledge bases, the sparse nature of KBs is often overlooked. To this end, we propose a case-based reasoning approach, CBR-iKB, for knowledge base question answering (KBQA) with incomplete-KB as our main focus. |
DUNG THAI et. al. | arxiv-cs.CL | 2022-04-18 |
| 187 | StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new Question-Answering dataset called StepGame for robust multi-hop spatial reasoning in texts. |
Zhengxiang Shi; Qiang Zhang; Aldo Lipani; | arxiv-cs.CL | 2022-04-18 |
| 188 | WikiOmnia: Generative QA Corpus on The Whole Russian Wikipedia Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present the WikiOmnia dataset, a new publicly available set of QA-pairs and corresponding Russian Wikipedia article summary sections, composed with a fully automated generative pipeline. |
Dina Pisarevskaya; Tatiana Shavrina; | arxiv-cs.CL | 2022-04-17 |
| 189 | ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present ArcaneQA, a novel generation-based model that addresses both the large search space and schema linking in a unified framework with two mutually boosting ingredients: we use dynamic program induction to tackle the large search space and dynamic contextualized encoding to enhance schema linking. |
Yu Gu; Yu Su; | arxiv-cs.CL | 2022-04-17 |
| 190 | Attention Mechanism Based Cognition-level Scene Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a parallel attention-based cognitive VCR network PAVCR, which fuses visual-textual information efficiently and encodes semantic information in parallel to enable the model to capture rich information for cognition-level inference. |
XUEJIAO TANG et. al. | arxiv-cs.CV | 2022-04-17 |
| 191 | Mixture of Experts for Biomedical Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, in order to alleviate the parameter competition problem, we propose a Mixture-of-Expert (MoE) based question answering method called MoEBQA that decouples the computation for different types of questions by sparse routing. |
DAMAI DAI et. al. | arxiv-cs.CL | 2022-04-15 |
| 192 | Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore one additional utility of the multi-hop decomposition from the perspective of explainable NLP: to create explanation by probing a neural QA model with them. |
Kaige Xie; Sarah Wiegreffe; Mark Riedl; | arxiv-cs.CL | 2022-04-15 |
| 193 | Towards Fine-grained Causal Reasoning and QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces a novel fine-grained causal reasoning dataset and presents a series of novel predictive tasks in NLP, such as causality detection, event causality extraction, and Causal QA. |
Linyi Yang; Zhen Wang; Yuxiang Wu; Jie Yang; Yue Zhang; | arxiv-cs.CL | 2022-04-15 |
| 194 | Semantic Structure Based Query Graph Prediction for Question Answering Over Knowledge Graph Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we define six semantic structures from common questions in KGQA and develop a novel Structure-BERT to predict the semantic structure of a question. |
Mingchen Li; Shihao Ji; | arxiv-cs.CL | 2022-04-15 |
| 195 | Improving Passage Retrieval with Zero-Shot Question Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a simple and effective re-ranking method for improving passage retrieval in open question answering. |
DEVENDRA SINGH SACHAN et. al. | arxiv-cs.CL | 2022-04-15 |
| 196 | Exploring Dual Encoder Architectures for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore the dual encoder architectures for QA retrieval tasks. |
ZHE DONG et. al. | arxiv-cs.CL | 2022-04-14 |
| 197 | XLMRQA: Open-Domain Question Answering on Vietnamese Wikipedia-based Textual Knowledge Source Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents XLMRQA, the first Vietnamese QA system using a supervised transformer-based reader on the Wikipedia-based textual knowledge source (using the UIT-ViQuAD corpus), outperforming the two robust QA systems using deep neural network models: DrQA and BERTserini with 24.46% and 6.28%, respectively. |
KIET VAN NGUYEN et. al. | arxiv-cs.CL | 2022-04-14 |
| 198 | Can Question Rewriting Help Conversational Question Answering? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We provide an analysis of the failure and describe the difficulty of exploiting QR for CQA. |
Etsuko Ishii; Yan Xu; Samuel Cahyawijaya; Bryan Wilie; | arxiv-cs.CL | 2022-04-13 |
| 199 | AGQA 2.0: An Updated Benchmark for Compositional Spatio-Temporal Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, some biases remain in several AGQA categories. We introduce AGQA 2.0, a version of this benchmark with several improvements, most namely a stricter balancing procedure. |
Madeleine Grunde-McLaughlin; Ranjay Krishna; Maneesh Agrawala; | arxiv-cs.CV | 2022-04-12 |
| 200 | ASQA: Factoid Questions Meet Long-Form Answers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: The hurdles include (i) a lack of high-quality data, and (ii) the absence of a well-defined notion of the answer’s quality. In this work, we address these problems by (i) releasing a novel dataset and a task that we call ASQA (Answer Summaries for Questions which are Ambiguous); and (ii) proposing a reliable metric for measuring performance on ASQA. |
Ivan Stelmakh; Yi Luan; Bhuwan Dhingra; Ming-Wei Chang; | arxiv-cs.CL | 2022-04-12 |
| 201 | MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we augment the QA samples of the target language using translation and transliteration into other languages and use the augmented data to fine-tune an mBERT-based QA model, which is already pre-trained in English. |
Gokul Karthik Kumar; Abhishek Singh Gehlot; Sahal Shaji Mullappilly; Karthik Nandakumar; | arxiv-cs.CL | 2022-04-12 |
| 202 | Solving Price Per Unit Problem Around The World: Formulating Fact Extraction As Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To predict total quantity, all relevant quantities given in a product attributes such as title, description and image need to be inferred correctly. We formulate this problem as a question-answering (QA) task rather than named entity recognition (NER) task for fact extraction. |
Tarik Arici; Kushal Kumar; Hayreddin Çeker; Anoop S V K K Saladi; Ismail Tutar; | arxiv-cs.CL | 2022-04-12 |
| 203 | Answering Count Queries with Explanatory Evidence Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a methodology for answering count queries with inference, contextualization and explanatory evidence. |
Shrestha Ghosh; Simon Razniewski; Gerhard Weikum; | arxiv-cs.IR | 2022-04-11 |
| 204 | Data Augmentation for Biomedical Factoid Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We study the effect of seven data augmentation (da) methods in factoid question answering, focusing on the biomedical domain, where obtaining training instances is particularly difficult. |
Dimitris Pappas; Prodromos Malakasiotis; Ion Androutsopoulos; | arxiv-cs.CL | 2022-04-10 |
| 205 | Breaking Character: Are Subwords Good Enough for MRLs After All? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We compare the resulting model, dubbed TavBERT, against contemporary PLMs based on subwords for three highly complex and ambiguous MRLs (Hebrew, Turkish, and Arabic), testing them on both morphological and semantic tasks. |
Omri Keren; Tal Avinari; Reut Tsarfaty; Omer Levy; | arxiv-cs.CL | 2022-04-10 |
| 206 | Extending The Scope of Out-of-Domain: Examining QA Models in Multiple Subdomains Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we extend the scope of out-of-domain by splitting QA examples into different subdomains according to their several internal characteristics including question type, text length, answer position. |
Chenyang Lyu; Jennifer Foster; Yvette Graham; | arxiv-cs.CL | 2022-04-09 |
| 207 | Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This yields an end-to-end system that not only outperforms prior QA retrieval methods on single-hop QA tasks but also enables compositional reasoning, as demonstrated by strong performance on two multi-hop QA datasets. Together, these methods improve the ability to interpret and control the model while narrowing the performance gap with passage retrieval systems. |
Wenhu Chen; Pat Verga; Michiel de Jong; John Wieting; William Cohen; | arxiv-cs.CL | 2022-04-09 |
| 208 | From Rewriting to Remembering: Common Ground for Conversational QA Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the Common Ground (CG), an approach to accumulate conversational information as it emerges and select the relevant information at every turn. |
Marco Del Tredici; Xiaoyu Shen; Gianni Barlacchi; Bill Byrne; Adrià de Gispert; | arxiv-cs.CL | 2022-04-08 |
| 209 | KGI: An Integrated Framework for Knowledge Intensive Language Tasks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In a recent work, we presented a novel state-of-the-art approach to zero-shot slot filling that extends dense passage retrieval with hard negatives and robust training procedures for retrieval augmented generation models. |
Md Faisal Mahbub Chowdhury; Michael Glass; Gaetano Rossiello; Alfio Gliozzo; Nandana Mihindukulasooriya; | arxiv-cs.CL | 2022-04-08 |
| 210 | RuBioRoBERTa: A Pre-trained Biomedical Language Model for Russian Language Biomedical Text Mining Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents several BERT-based models for Russian language biomedical text mining (RuBioBERT, RuBioRoBERTa). |
Alexander Yalunin; Alexander Nesterov; Dmitriy Umerenkov; | arxiv-cs.CL | 2022-04-08 |
| 211 | Parameter-Efficient Abstractive Question Answering Over Tables or Text Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we study parameter-efficient abstractive QA in encoder-decoder models over structured tabular data and unstructured textual data using only 1.5% additional parameters for each modality. |
Vaishali Pal; Evangelos Kanoulas; Maarten de Rijke; | arxiv-cs.CL | 2022-04-07 |
| 212 | Using Interactive Feedback to Improve The Accuracy and Explainability of Question Answering Systems Post-Deployment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we ask the question: Can we improve QA systems further \emph{post-}deployment based on user interactions? |
Zichao Li; Prakhar Sharma; Xing Han Lu; Jackie C. K. Cheung; Siva Reddy; | arxiv-cs.CL | 2022-04-06 |
| 213 | Improved and Efficient Conversational Slot Labeling Through Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we focus on modeling and studying \textit{slot labeling} (SL), a crucial component of NLU for dialog, through the QA optics, aiming to improve both its performance and efficiency, and make it more effective and resilient to working with limited task data. To this end, we make a series of contributions: 1) We demonstrate how QA-tuned PLMs can be applied to the SL task, reaching new state-of-the-art performance, with large gains especially pronounced in such low-data regimes. |
Gabor Fuisz; Ivan Vulić; Samuel Gibbons; Inigo Casanueva; Paweł Budzianowski; | arxiv-cs.CL | 2022-04-05 |
| 214 | CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To obtain detailed insights into the process of generating natural language explanations for VQA, we introduce the large-scale CLEVR-X dataset that extends the CLEVR dataset with natural language explanations. |
Leonard Salewski; A. Sophia Koepke; Hendrik P. A. Lensch; Zeynep Akata; | arxiv-cs.CV | 2022-04-05 |
| 215 | Co-VQA : Answering By Interactive Sub Question Sequence Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: By simulating the process, this paper proposes a conversation-based VQA (Co-VQA) framework, which consists of three components: Questioner, Oracle, and Answerer. |
Ruonan Wang; Yuxi Qian; Fangxiang Feng; Xiaojie Wang; Huixing Jiang; | arxiv-cs.CL | 2022-04-02 |
| 216 | Question-Driven Graph Fusion Network For Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address the problem, we propose a Question-Driven Graph Fusion Network (QD-GFN). |
Yuxi Qian; Yuncong Hu; Ruonan Wang; Fangxiang Feng; Xiaojie Wang; | arxiv-cs.CV | 2022-04-02 |
| 217 | Efficient Comparison of Sentence Embeddings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we will discuss about various word and sentence embeddings algorithms, we will select a sentence embedding algorithm, BERT, as our algorithm of choice and we will evaluate the performance of two vector comparison approaches, FAISS and Elasticsearch, in the specific problem of sentence embeddings. |
Spyros Zoupanos; Stratis Kolovos; Athanasios Kanavos; Orestis Papadimitriou; Manolis Maragoudakis; | arxiv-cs.CL | 2022-04-02 |
| 218 | Multifaceted Improvements for Conversational Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate these limitations, in this paper, we propose a framework with Multifaceted Improvements for Conversational open-domain Question Answering (MICQA). |
TINGTING LIANG et. al. | arxiv-cs.CL | 2022-04-01 |
| 219 | Syntax-informed Question Answering with Heterogeneous Graph Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a linguistics-informed question answering approach that extends and fine-tunes a pre-trained transformer-based neural language model with symbolic knowledge encoded with a heterogeneous graph transformer. |
Fangyi Zhu; Lok You Tan; See-Kiong Ng; Stéphane Bressan; | arxiv-cs.CL | 2022-04-01 |
| 220 | End-to-End Table Question Answering Via Retrieval-Augmented Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate this problem, we introduce T-RAG, an end-to-end Table QA model, where a non-parametric dense vector index is fine-tuned jointly with BART, a parametric sequence-to-sequence model to generate answer tokens. |
Feifei Pan; Mustafa Canim; Michael Glass; Alfio Gliozzo; James Hendler; | arxiv-cs.CL | 2022-03-30 |
| 221 | Towards Differential Relational Privacy and Its Use in Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce Relational Memorization (RM) to understand, quantify and control this phenomenon. |
SIMONE BOMBARI et. al. | arxiv-cs.LG | 2022-03-30 |
| 222 | Auto-MLM: Improved Contrastive Learning for Self-supervised Multi-lingual Knowledge Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To optimize the CL hardly obtain internal information from the original query, we introduce a joint training method by combining CL and Auto-MLM for self-supervised multi-lingual knowledge retrieval. |
Wenshen Xu; Mieradilijiang Maimaiti; Yuanhang Zheng; Xin Tang; Ji Zhang; | arxiv-cs.CL | 2022-03-30 |
| 223 | Survival Analysis for User Disengagement Prediction: Question-and-answering Communities’ Case Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We used survival analysis to model user disengagement in three distinct questions-and-answering communities in this work. |
Hassan Abedi Firouzjaei; | arxiv-cs.SI | 2022-03-29 |
| 224 | ANNA: Enhanced Language Representation for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate how the approaches affect performance individually, and that the language model performs the best results on a specific question answering task when those approaches are jointly considered in pre-training models. |
CHANGWOOK JUN et. al. | arxiv-cs.CL | 2022-03-28 |
| 225 | MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces MedMCQA, a new large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. |
Ankit Pal; Logesh Kumar Umapathi; Malaikannan Sankarasubbu; | arxiv-cs.CL | 2022-03-27 |
| 226 | MQDD: Pre-training of Multimodal Question Duplicity Detection for Software Engineering Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes a new pipeline for leveraging data collected on the Stack Overflow website for pre-training a multimodal model for searching duplicates on question answering websites. |
Jan Pašek; Jakub Sido; Miloslav Konopík; Ondřej Pražák; | arxiv-cs.CL | 2022-03-26 |
| 227 | UKP-SQUARE: An Online Platform for Question Answering Research Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, we present UKP-SQUARE, an extensible online QA platform for researchers which allows users to query and analyze a large collection of modern Skills via a user-friendly web interface and integrated behavioural tests. |
TIM BAUMGÄRTNER et. al. | arxiv-cs.CL | 2022-03-25 |
| 228 | Improving Question Answering Over Knowledge Graphs Using Graph Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrated the proposed technique on the most common type of questions, which is single-relation questions. |
Sirui Li; Kok Kai Wong; Dengya Zhu; Chun Che Fung; | arxiv-cs.LG | 2022-03-25 |
| 229 | Fantastic Questions and Where to Find Them: FairytaleQA — An Authentic Dataset for Narrative Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Drawing on the reading education research, we introduce FairytaleQA, a dataset focusing on narrative comprehension of kindergarten to eighth-grade students. |
YING XU et. al. | arxiv-cs.CL | 2022-03-25 |
| 230 | Towards Escaping from Language Bias and OCR Error: Semantics-Centered Text Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel Semantics-Centered Network (SC-Net) that consists of an instance-level contrastive semantic prediction module (ICSP) and a semantics-centered transformer module (SCT). |
CHENGYANG FANG et. al. | arxiv-cs.CV | 2022-03-24 |
| 231 | A Theoretically Grounded Benchmark for Evaluating Machine Commonsense Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these challenges, we propose a benchmark called Theoretically-Grounded Commonsense Reasoning (TG-CSR) that is also based on discriminative question answering, but with questions designed to evaluate diverse aspects of commonsense, such as space, time, and world states. |
HENRIQUE SANTOS et. al. | arxiv-cs.CL | 2022-03-23 |
| 232 | Towards Efficient and Elastic Visual Question Answering with Doubly Slimmable Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the Doubly Slimmable Transformer (DST), a general framework that can be seamlessly integrated into arbitrary Transformer-based VQA models to train one single model once and obtain various slimmed submodels of different widths and depths. |
Zhou Yu; Zitian Jin; Jun Yu; Mingliang Xu; Jianping Fan; | arxiv-cs.CV | 2022-03-23 |
| 233 | Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a hybrid classical-quantum framework based on the Frank-Wolfe algorithm, Q-FW, for solving quadratic, linearly-constrained, binary optimization problems on quantum annealers (QA). |
Alp Yurtsever; Tolga Birdal; Vladislav Golyanik; | arxiv-cs.CV | 2022-03-23 |
| 234 | Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering Over Knowledge Bases Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address this particular challenge for systems handling a specific category of questions called temporal questions, where answer derivation involve reasoning over facts asserting point/intervals of time for various events. |
NITHISH KANNEN et. al. | arxiv-cs.CL | 2022-03-21 |
| 235 | Teaching Language Models to Support Answers with Verified Quotes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we use reinforcement learning from human preferences (RLHP) to train open-book QA models that generate answers whilst also citing specific evidence for their claims, which aids in the appraisal of correctness. |
JACOB MENICK et. al. | arxiv-cs.CL | 2022-03-21 |
| 236 | VLSP 2021 – ViMRC Challenge: Vietnamese Machine Reading Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we present details of the organization of the challenge, an overview of the methods employed by shared-task participants, and the results. |
KIET VAN NGUYEN et. al. | arxiv-cs.CL | 2022-03-21 |
| 237 | Programming Language Agnostic Mining of Code and Language Pairs with Sequence Labeling Based Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Sequence Labeling based Question Answering (SLQA) method to mine NL-PL pairs in a PL-agnostic manner. |
Changran Hu; Akshara Reddi Methukupalli; Yutong Zhou; Chen Wu; Yubo Chen; | arxiv-cs.CL | 2022-03-21 |
| 238 | Calibration of Machine Reading Systems at Scale Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present an investigation into calibrating open setting machine reading systems such as open-domain question answering and claim verification systems. |
Shehzaad Dhuliawala; Leonard Adolphs; Rajarshi Das; Mrinmaya Sachan; | arxiv-cs.CL | 2022-03-20 |
| 239 | A Neural-Symbolic Approach to Natural Language Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by the theory, we present a novel framework for NLU called Neural-Symbolic Processor (NSP), which performs analogical reasoning based on neural processing and performs logical reasoning based on both neural and symbolic processing. |
Zhixuan Liu; Zihao Wang; Yuan Lin; Hang Li; | arxiv-cs.CL | 2022-03-20 |
| 240 | ChartQA: A Benchmark for Question Answering About Charts with Visual and Logical Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we present a large-scale benchmark covering 9.6K human-written questions as well as 23.1K questions generated from human-written chart summaries. |
Ahmed Masry; Do Xuan Long; Jia Qing Tan; Shafiq Joty; Enamul Hoque; | arxiv-cs.CL | 2022-03-19 |
| 241 | Clickbait Spoiling Via Question Answering and Passage Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce and study the task of clickbait spoiling: generating a short text that satisfies the curiosity induced by a clickbait post. |
Matthias Hagen; Maik Fröbe; Artur Jurk; Martin Potthast; | arxiv-cs.CL | 2022-03-19 |
| 242 | Ask to Understand: Question Generation for Multi-hop Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel method to complete multi-hop QA from the perspective of Question Generation (QG). |
Jiawei Li; Mucheng Ren; Yang Gao; Yizhe Yang; | arxiv-cs.CL | 2022-03-17 |
| 243 | ElBERto: Self-supervised Commonsense Learning for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Self-supervised Bidirectional Encoder Representation Learning of Commonsense (elBERto) framework, which is compatible with off-the-shelf QA model architectures. |
XUNLIN ZHAN et. al. | arxiv-cs.CL | 2022-03-17 |
| 244 | DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we implement an efficient, data-programming technique that enriches training data with KB-derived context and improves transformer utilization of encoded knowledge when fine-tuning for a particular QA task, namely answer sentence selection (AS2). |
Nic Jedema; Thuy Vu; Manish Gupta; Alessandro Moschitti; | arxiv-cs.CL | 2022-03-17 |
| 245 | E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Holding the belief that models capable of reasoning should be right for the right reasons, we propose a first-of-its-kind Explainable Knowledge-intensive Analogical Reasoning benchmark (E-KAR). |
JIANGJIE CHEN et. al. | arxiv-cs.CL | 2022-03-16 |
| 246 | Uncertainty-Aware Text-to-Program for Question Answering on Structured Electronic Health Records Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we design the program-based model (NLQ2Program) for EHR-QA as the first step towards the future direction. |
Daeyoung Kim; Seongsu Bae; Seungho Kim; Edward Choi; | arxiv-cs.CL | 2022-03-14 |
| 247 | Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To be aligned with the state-of-the-art, we explore nine transformer-based large pre-trained language models (PrLMs) as backbone architectures. |
MAN LUO et. al. | arxiv-cs.CL | 2022-03-14 |
| 248 | ScienceWorld: Is Your Agent Smarter Than A 5th Grader? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a new benchmark, ScienceWorld, to test agents’ scientific reasoning abilities in a new interactive text environment at the level of a standard elementary school science curriculum. |
Ruoyao Wang; Peter Jansen; Marc-Alexandre Côté; Prithviraj Ammanabrolu; | arxiv-cs.CL | 2022-03-14 |
| 249 | CLIP Models Are Few-shot Learners: Empirical Studies on VQA and Visual Entailment Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we empirically show that CLIP can be a strong vision-language few-shot learner by leveraging the power of language. |
Haoyu Song; Li Dong; Wei-Nan Zhang; Ting Liu; Furu Wei; | arxiv-cs.CV | 2022-03-14 |
| 250 | Towards Semantic Search for Community Question Answering for Mortgage Officers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We aim to publish the internally-annotated evaluation and training datasets in the near future. |
Amir Reza Rahmani; Linwei Li; Brian Vanover; Colin Bertrand; Shourabh Rawat; | arxiv-cs.IR | 2022-03-13 |
| 251 | Towards Visual-Prompt Temporal Answering Grounding in Medical Instructional Video Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge these gaps, we propose a visual-prompt text span localizing (VPTSL) method, which introduces the timestamped subtitles as a passage to perform the text span localization for the input text question, and prompts the visual highlight features into the pre-trained language model (PLM) for enhancing the joint semantic representations. |
Bin Li; Yixuan Weng; Bin Sun; Shutao Li; | arxiv-cs.CV | 2022-03-13 |
| 252 | Cross-lingual Inference with A Chinese Entailment Graph Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the first pipeline for building Chinese entailment graphs, which involves a novel high-recall open relation extraction (ORE) method and the first Chinese fine-grained entity typing dataset under the FIGER type ontology. |
Tianyi Li; Sabine Weber; Mohammad Javad Hosseini; Liane Guillou; Mark Steedman; | arxiv-cs.CL | 2022-03-11 |
| 253 | DUAL: Discrete Spoken Unit Adaptive Learning for Textless Spoken Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work proposes Discrete Spoken Unit Adaptive Learning (DUAL), leveraging unlabeled data for pre-training and fine-tuned by the SQA downstream task. |
GUAN-TING LIN et. al. | arxiv-cs.CL | 2022-03-09 |
| 254 | Internet-augmented Language Models Through Few-shot Prompting for Open-domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we aim to capitalize on the unique few-shot capabilities of large-scale language models (LSLMs) to overcome some of their challenges with respect to grounding to factual and up-to-date information. |
Angeliki Lazaridou; Elena Gribovskaya; Wojciech Stokowiec; Nikolai Grigorev; | arxiv-cs.CL | 2022-03-09 |
| 255 | Barlow Constrained Optimization for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel regularization for VQA models, Constrained Optimization using Barlow’s theory (COB), that improves the information content of the joint space by minimizing the redundancy. |
Abhishek Jha; Badri N. Patro; Luc Van Gool; Tinne Tuytelaars; | arxiv-cs.CV | 2022-03-07 |
| 256 | Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a simple yet effective training strategy for text semantic matching in a divide-and-conquer manner by disentangling keywords from intents. |
YICHENG ZOU et. al. | arxiv-cs.CL | 2022-03-06 |
| 257 | Dynamic Key-value Memory Enhanced Multi-step Graph Reasoning for Knowledge-based Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel model named dynamic knowledge memory enhanced multi-step graph reasoning (DMMGR), which performs explicit and implicit reasoning over a key-value knowledge memory module and a spatial-aware image graph, respectively. |
Mingxiao Li; Marie-Francine Moens; | arxiv-cs.CV | 2022-03-06 |
| 258 | QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we address these shortcomings by proposing a new prompt-based learning NER method with Question Answering (QA), called QaNER. |
ANDY T. LIU et. al. | arxiv-cs.CL | 2022-03-03 |
| 259 | Video Question Answering: Datasets, Algorithms and Challenges Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper thus provides a clear taxonomy and comprehensive analyses to VideoQA, focusing on the datasets, algorithms, and unique challenges. |
YAOYAO ZHONG et. al. | arxiv-cs.CV | 2022-03-02 |
| 260 | Read Before Generate! Faithful Long Form Question Answering with Machine Reading Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a new end-to-end framework that jointly models answer generation and machine reading. |
DAN SU et. al. | arxiv-cs.CL | 2022-03-01 |
| 261 | Recent, Rapid Advancement in Visual Question Answering Architecture: A Review Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Several points on the benefits of visual question answering are mentioned in the review paper by Manmadhan et al. (2020), on which the present article builds, including subsequent updates in the field. |
Venkat Kodali; Daniel Berleant; | arxiv-cs.CV | 2022-03-01 |
| 262 | Improving Lexical Embeddings for Robust Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To strengthen the robustness of QA models and their generalization ability, we propose a representation Enhancement via Semantic and Context constraints (ESC) approach to improve the robustness of lexical embeddings. |
Weiwen Xu; Bowei Zou; Wai Lam; Ai Ti Aw; | arxiv-cs.CL | 2022-02-28 |
| 263 | ‘Tis But Thy Name: Semantic Question Answering Evaluation with 11M Names for 1M Entities Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the Wiki Entity Similarity (WES) dataset, an 11M example, domain targeted, semantic entity similarity dataset that is generated from link texts in Wikipedia. |
Albert Huang; | arxiv-cs.CL | 2022-02-28 |
| 264 | Semantic Sentence Composition Reasoning for Multi-Hop Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To alleviate the challenges of semantic factual sentences retrieval and multi-hop context expansion, we present a semantic sentence composition reasoning approach for a multi-hop question answering task, which consists of two key modules: a multi-stage semantic matching module (MSSM) and a factual sentence composition module (FSC). |
Qianglong Chen; | arxiv-cs.CL | 2022-02-28 |
| 265 | A Generative Model for Relation Extraction and Classification Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel generative model for relation extraction and classification (which we call GREC), where RE is modeled as a sequence-to-sequence generation task. |
Jian Ni; Gaetano Rossiello; Alfio Gliozzo; Radu Florian; | arxiv-cs.CL | 2022-02-26 |
| 266 | Joint Answering and Explanation for Visual Commonsense Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on our findings, in this paper, we present a plug-and-play knowledge distillation enhanced framework to couple the question answering and rationale inference processes. |
ZHENYANG LI et. al. | arxiv-cs.CV | 2022-02-25 |
| 267 | BERTVision — A Parameter-Efficient Approach for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a highly parameter efficient approach for Question Answering that significantly reduces the need for extended BERT fine-tuning. |
Siduo Jiang; Cristopher Benge; William Casey King; | arxiv-cs.CL | 2022-02-24 |
| 268 | Measuring CLEVRness: Blackbox Testing of Visual Reasoning Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To answer this, we extend the visual question answering framework and propose the following behavioral test in the form of a two-player game. |
Spyridon Mouselinos; Henryk Michalewski; Mateusz Malinowski; | arxiv-cs.LG | 2022-02-24 |
| 269 | Knowledge Base Question Answering By Case-based Reasoning Over Subgraphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, we hypothesize in a large KB, reasoning patterns required to answer a query type reoccur for various entities in their respective subgraph neighborhoods. Leveraging this structural similarity between local neighborhoods of different subgraphs, we introduce a semiparametric model (CBR-SUBG) with (i) a nonparametric component that for each query, dynamically retrieves other similar $k$-nearest neighbor (KNN) training queries along with query-specific subgraphs and (ii) a parametric component that is trained to identify the (latent) reasoning patterns from the subgraphs of KNN queries and then apply them to the subgraph of the target query. |
RAJARSHI DAS et. al. | arxiv-cs.CL | 2022-02-21 |
| 270 | (2.5+1)D Spatio-Temporal Scene Graphs for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Leveraging this insight, we propose a (2.5+1)D scene graph representation to better capture the spatio-temporal information flows inside the videos. |
Anoop Cherian; Chiori Hori; Tim K. Marks; Jonathan Le Roux; | arxiv-cs.CV | 2022-02-18 |
| 271 | Discovering Fine-Grained Semantics in Knowledge Graph Relations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we provide a strategy for discovering the different semantics associated with abstract relations and deriving many sub-relations with fine-grained meaning. |
Nitisha Jain; Ralf Krestel; | arxiv-cs.AI | 2022-02-17 |
| 272 | ZeroGen: Efficient Zero-shot Learning Via Dataset Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study a flexible and efficient zero-short learning method, ZeroGen. |
JIACHENG YE et. al. | arxiv-cs.CL | 2022-02-16 |
| 273 | Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the first systematic conceptual and data-driven analysis to examine the shortcomings of token-level equivalence measures. |
Jannis Bulian; Christian Buck; Wojciech Gajewski; Benjamin Boerschinger; Tal Schuster; | arxiv-cs.CL | 2022-02-15 |
| 274 | Privacy Preserving Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel privacy-preserving methodology for performing Visual Question Answering on the edge. |
CRISTIAN-PAUL BARA et. al. | arxiv-cs.CV | 2022-02-15 |
| 275 | Delving Deeper Into Cross-lingual Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we delve deeper and address different aspects of cross-lingual VQA holistically, aiming to understand the impact of input data, fine-tuning and evaluation regimes, and interactions between the two modalities in cross-lingual setups. |
Chen Liu; Jonas Pfeiffer; Anna Korhonen; Ivan Vulic; Iryna Gurevych; | arxiv-cs.CL | 2022-02-15 |
| 276 | An Experimental Study of The Vision-bottleneck in VQA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an in-depth study of the vision-bottleneck in VQA, experimenting with both the quantity and quality of visual objects extracted from images. |
Pierre Marza; Corentin Kervadec; Grigory Antipov; Moez Baccouche; Christian Wolf; | arxiv-cs.CV | 2022-02-14 |
| 277 | QA4QG: Using Question Answering to Constrain Multi-Hop Question Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this work, we propose a novel framework, QA4QG, a QA-augmented BART-based framework for MQG. |
Dan Su; Peng Xu; Pascale Fung; | arxiv-cs.CL | 2022-02-14 |
| 278 | On The Relationship Between Shy and Warded Datalog+/- Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For this reason, different fragments have emerged, introducing syntactic limitations to Datalog^E that strike a balance between its expressive power and the computational complexity of QA, to achieve decidability. In this short paper, we focus on two promising tractable candidates, namely Shy and Warded Datalog+/-. |
Teodoro Baldazzi; Luigi Bellomarini; Marco Favorito; Emanuel Sallinger; | arxiv-cs.LO | 2022-02-13 |
| 279 | PQuAD: A Persian Question Answering Dataset Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Persian Question Answering Dataset (PQuAD), a crowdsourced reading comprehension dataset on Persian Wikipedia articles. |
Kasra Darvishi; Newsha Shahbodagh; Zahra Abbasiantaeb; Saeedeh Momtazi; | arxiv-cs.CL | 2022-02-13 |
| 280 | Recognition-free Question Answering on Handwritten Document Collections Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this problem, we propose a recognition-free QA approach, especially designed for handwritten document image collections. |
Oliver Tüselmann; Friedrich Müller; Fabian Wolf; Gernot A. Fink; | arxiv-cs.CV | 2022-02-12 |
| 281 | Can Open Domain Question Answering Systems Answer Visual Knowledge Questions? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a potentially data-efficient approach that reuses existing systems for (a) image analysis, (b) question rewriting, and (c) text-based question answering to answer such visual questions. |
Jiawen Zhang; Abhijit Mishra; Avinesh P. V. S; Siddharth Patwardhan; Sachin Agarwal; | arxiv-cs.AI | 2022-02-09 |
| 282 | FedQAS: Privacy-aware Machine Reading Comprehension with Federated Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, we present FedQAS, a privacy-preserving machine reading system capable of leveraging large-scale private data without the need to pool those datasets in a central location. |
Addi Ait-Mlouk; Sadi Alawadi; Salman Toor; Andreas Hellander; | arxiv-cs.CL | 2022-02-09 |
| 283 | Integrating Question Answering and Text-to-SQL in Portuguese Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We implemented a complete system for the Portuguese language, using some of the main tools available for the language and translating training and testing datasets. |
Marcos Menon José; Marcelo Archanjo José; Denis Deratani Mauá; Fábio Gagliardi Cozman; | arxiv-cs.CL | 2022-02-08 |
| 284 | GreaseLM: Graph REASoning Enhanced Language Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose GreaseLM, a new model that fuses encoded representations from pretrained LMs and GNNs over multiple layers of modality interaction operations, allowing both modalities to bidirectionally inform the representation of the other. |
XIKUN ZHANG et. al. | iclr | 2022-02-08 |
| 285 | Mention Memory: Incorporating Textual Knowledge Into Transformers Through Entity Mention Attention Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Incorporate information from text corpus into Transformer model through within-model attention over table of entity mention representations. |
Michiel de Jong; Yury Zemlyanskiy; Nicholas FitzGerald; Fei Sha; William W. Cohen; | iclr | 2022-02-08 |
| 286 | GNN Is A Counter? Revisiting GNN for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Counting is essential for reasoning and our simplistic graph neural counter is efficient and effective for QA tasks. |
Kuan Wang; Yuyu Zhang; Diyi Yang; Le Song; Tao Qin; | iclr | 2022-02-08 |
| 287 | Measuring CLEVRness: Black-box Testing of Visual Reasoning Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Black box testing of visual reasoning models as a two-player game. |
Spyridon Mouselinos; Henryk Michalewski; Mateusz Malinowski; | iclr | 2022-02-08 |
| 288 | NEWSKVQA: Knowledge-Aware News Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore a new frontier in video question answering: answering knowledge-based questions in the context of news videos. |
Pranay Gupta; Manish Gupta; | arxiv-cs.CV | 2022-02-08 |
| 289 | Interactive Mobile App Navigation with Uncertain or Under-specified Natural Language Commands Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce task feasibility prediction and propose an initial model which obtains an F1 score of 61.1. |
ANDREA BURNS et. al. | arxiv-cs.CL | 2022-02-04 |
| 290 | Pirá: A Bilingual Portuguese-English Dataset for Question-Answering About The Ocean Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents the Pir\’a dataset, a large set of questions and answers about the ocean and the Brazilian coast both in Portuguese and English. |
ANDRÉ F. A. PASCHOAL et. al. | arxiv-cs.CL | 2022-02-04 |
| 291 | JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the Japanese Question Answering Dataset, JaQuAD, which is annotated by humans. |
ByungHoon So; Kyuhong Byun; Kyungwon Kang; Seongjin Cho; | arxiv-cs.CL | 2022-02-03 |
| 292 | GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We developed GatorTron models from scratch using the BERT architecture of different sizes including 345 million, 3.9 billion, and 8.9 billion parameters, compared GatorTron with three existing transformer models in the clinical and biomedical domain on 5 different clinical NLP tasks including clinical concept extraction, relation extraction, semantic textual similarity, natural language inference, and medical question answering, to examine how large transformer models could help clinical NLP at different linguistic levels. |
XI YANG et. al. | arxiv-cs.CL | 2022-02-02 |
| 293 | Research on Question Classification Methods in The Medical Field Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Question classification is one of the important links in the research of question and answering system. |
Jinzhang Liu; | arxiv-cs.CL | 2022-02-01 |
| 294 | QALD-9-plus: A Multilingual Dataset for Question Answering Over DBpedia and Wikidata Translated By Native Speakers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we extend one of the most popular KGQA benchmarks – QALD-9 by introducing high-quality questions’ translations to 8 languages provided by native speakers, and transferring the SPARQL queries of QALD-9 from DBpedia to Wikidata, s.t., the usability and relevance of the dataset is strongly increased. |
Aleksandr Perevalov; Dennis Diefenbach; Ricardo Usbeck; Andreas Both; | arxiv-cs.CL | 2022-01-31 |
| 295 | Semantic Annotation and Querying Framework Based on Semi-structured Ayurvedic Text Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, in this work, we describe our efforts on manual annotation of Sanskrit text for the purpose of knowledge graph (KG) creation. |
Hrishikesh Terdalkar; Arnab Bhattacharya; Madhulika Dubey; Ramamurthy S; Bhavna Naneria Singh; | arxiv-cs.IR | 2022-01-31 |
| 296 | Compositionality As Lexical Symmetry Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a domain-general framework for compositional modeling that instead formulates compositionality as a constraint on data distributions. |
Ekin Akyürek; Jacob Andreas; | arxiv-cs.CL | 2022-01-30 |
| 297 | Transformer Module Networks for Systematic Generalization in Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Inspired by Transformers and NMNs, we propose Transformer Module Network (TMN), a novel Transformer-based model for VQA that dynamically composes modules into a question-specific Transformer network. |
Moyuru Yamada; Vanessa D’Amario; Kentaro Takemoto; Xavier Boix; Tomotake Sasaki; | arxiv-cs.CV | 2022-01-26 |
| 298 | Addressing Issues of Cross-Linguality in Open-Retrieval Question Answering Systems For Emergent Domains Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate a cross-lingual open-retrieval question answering system for the emergent domain of COVID-19. |
Alon Albalak; Sharon Levy; William Yang Wang; | arxiv-cs.CL | 2022-01-26 |
| 299 | An Automated Question-Answering Framework Based on Evolution Algorithm Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an automated Question-Answering framework, which could automatically adjust network architecture for multiple datasets. |
Sinan Tan; Hui Xue; Qiyu Ren; Huaping Liu; Jing Bai; | arxiv-cs.CL | 2022-01-26 |
| 300 | SCAI-QReCC Shared Task on Conversational Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Since all of the participant teams experimented with answer generation models for this task, we identified evaluation of answer correctness in this settings as the major challenge and a current research gap. |
Svitlana Vakulenko; Johannes Kiesel; Maik Fröbe; | arxiv-cs.IR | 2022-01-26 |
| 301 | DOM-LM: Learning Generalizable Representations for HTML Documents Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel representation learning approach for web pages, dubbed DOM-LM, which addresses the limitations of existing approaches by encoding both text and DOM tree structure with a transformer-based encoder and learning generalizable representations for HTML documents via self-supervised pre-training. |
Xiang Deng; Prashant Shiralkar; Colin Lockard; Binxuan Huang; Huan Sun; | arxiv-cs.CL | 2022-01-25 |
| 302 | MGA-VQA: Multi-Granularity Alignment for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Multi-Granularity Alignment architecture for Visual Question Answering task (MGA-VQA), which learns intra- and inter-modality correlations by multi-granularity alignment, and outputs the final result by the decision fusion module. |
Peixi Xiong; Yilin Shen; Hongxia Jin; | arxiv-cs.CV | 2022-01-25 |
| 303 | SA-VQA: Structured Alignment of Visual and Semantic Representations for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we attempt to solve this issue by first converting different modality entities into sequential nodes and the adjacency graph, then incorporating them for structured alignments. |
Peixi Xiong; Quanzeng You; Pei Yu; Zicheng Liu; Ying Wu; | arxiv-cs.CV | 2022-01-25 |
| 304 | Question Generation for Evaluating Cross-Dataset Shifts in Multi-modal Grounding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Visual question answering (VQA) is the multi-modal task of answering natural language questions about an input image. Through cross-dataset adaptation methods, it is possible to … |
Arjun R. Akula; | arxiv-cs.CV | 2022-01-24 |
| 305 | Artefact Retrieval: Overview of NLP Models with Knowledge Base Access Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we systematically describe the typology of artefacts (items retrieved from a knowledge base), retrieval mechanisms and the way these artefacts are fused into the model. |
Vilém Zouhar; Marius Mosbach; Debanjali Biswas; Dietrich Klakow; | arxiv-cs.CL | 2022-01-24 |
| 306 | Towards Collaborative Question Answering: A Preliminary Study Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose CollabQA, a novel QA task in which several expert agents coordinated by a moderator work together to answer questions that cannot be answered with any single agent alone. |
XIANGKUN HU et. al. | arxiv-cs.AI | 2022-01-24 |
| 307 | Leaf: Multiple-Choice Question Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this challenge, we present Leaf, a system for generating multiple-choice questions from factual text. |
KRISTIYAN VACHEV et. al. | arxiv-cs.CL | 2022-01-22 |
| 308 | Question Rewriting? Assessing Its Importance for Conversational Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents a conversational question answering system designed specifically for the Search-Oriented Conversational AI (SCAI) shared task, and reports on a detailed analysis of its question rewriting module. |
Gonçalo Raposo; Rui Ribeiro; Bruno Martins; Luísa Coheur; | arxiv-cs.CL | 2022-01-22 |
| 309 | Conversational Information Seeking Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our aim is to provide an overview of past research related to CIS, introduce the current state-of-the-art in CIS, highlight the challenges still being faced in the community. |
Hamed Zamani; Johanne R. Trippas; Jeff Dalton; Filip Radlinski; | arxiv-cs.IR | 2022-01-21 |
| 310 | GreaseLM: Graph REASoning Enhanced Language Models for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose GreaseLM, a new model that fuses encoded representations from pretrained LMs and graph neural networks over multiple layers of modality interaction operations. |
XIKUN ZHANG et. al. | arxiv-cs.CL | 2022-01-21 |
| 311 | Knowledge Graph Question Answering Leaderboard: A Community Resource to Prevent A Replication Crisis Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we survey and analyze a wide range of evaluation results with significant coverage of 100 publications and 98 systems from the last decade. |
ALEKSANDR PEREVALOV et. al. | arxiv-cs.CL | 2022-01-20 |
| 312 | Improving Biomedical Information Retrieval with Neural Retrievers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we seek to improve information retrieval (IR) using neural retrievers (NR) in the biomedical domain, and achieve this goal using a three-pronged approach. |
Man Luo; Arindam Mitra; Tejas Gokhale; Chitta Baral; | arxiv-cs.IR | 2022-01-19 |
| 313 | Evaluating Machine Common Sense Via Cloze Testing Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the use of cloze testing combined with word embeddings to measure the LM’s robustness and confidence. |
Ehsan Qasemi; Lee Kezar; Jay Pujara; Pedro Szekely; | arxiv-cs.CL | 2022-01-19 |
| 314 | Expert Finding in Legal Community Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose methods for generating query-dependent textual profiles for lawyers covering several aspects including sentiment, comments, and recency. |
Arian Askari; Suzan Verberne; Gabriella Pasi; | arxiv-cs.IR | 2022-01-19 |
| 315 | Korean-Specific Dataset for Table Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate how we construct Korean-specific datasets for table question answering: Korean tabular dataset is a collection of 1.4M tables with corresponding descriptions for unsupervised pre-training language models. |
CHANGWOOK JUN et. al. | arxiv-cs.CL | 2022-01-17 |
| 316 | Generalizable Neuro-symbolic Systems for Commonsense Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This chapter illustrates how suitable neuro-symbolic models for language understanding can enable domain generalizability and robustness in downstream tasks. |
Alessandro Oltramari; Jonathan Francis; Filip Ilievski; Kaixin Ma; Roshanak Mirzaee; | arxiv-cs.CL | 2022-01-17 |
| 317 | Natural Language Deduction Through Search Over Statement Compositions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a system for natural language deduction that decomposes the task into separate steps coordinated by best-first search, producing a tree of intermediate conclusions that faithfully reflects the system’s reasoning process. |
Kaj Bostrom; Zayne Sprague; Swarat Chaudhuri; Greg Durrett; | arxiv-cs.CL | 2022-01-16 |
| 318 | In Situ Answer Sentence Selection at Web-scale Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present Passage-based Extracting Answer Sentence In-place (PEASI), a novel design for AS2 optimized for Web-scale setting, that, instead, computes such answer without processing each candidate individually. |
Zeyu Zhang; Thuy Vu; Alessandro Moschitti; | arxiv-cs.CL | 2022-01-16 |
| 319 | Double Retrieval and Ranking for Accurate Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address both drawbacks by proposing (i) a double reranking model, which, for each target answer, selects the best support; and (ii) a second neural retrieval stage designed to encode question and answer pair as the query, which finds more specific verification information. |
Zeyu Zhang; Thuy Vu; Alessandro Moschitti; | arxiv-cs.CL | 2022-01-16 |
| 320 | A Benchmark for Generalizable and Interpretable Temporal Question Answering Over Knowledge Bases Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a benchmark dataset for temporal reasoning, TempQA-WD, to encourage research in extending the present approaches to target a more challenging set of complex reasoning tasks. |
SUMIT NEELAM et. al. | arxiv-cs.CL | 2022-01-15 |
| 321 | Ensemble Transformer for Efficient and Accurate Ranking Tasks: An Application to Question Answering Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we explore the following research question: How can we make the AS2models more accurate without significantly increasing their model complexity? |
Yoshitomo Matsubara; Luca Soldaini; Eric Lind; Alessandro Moschitti; | arxiv-cs.CL | 2022-01-15 |
| 322 | Reasoning Over Hybrid Chain for Table-and-Text Open Domain QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a ChAin-centric Reasoning and Pre-training framework (CARP). |
WANJUN ZHONG et. al. | arxiv-cs.CL | 2022-01-15 |
| 323 | Kformer: Knowledge Injection in Transformer Feed-Forward Layers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore the FFN in Transformer and propose a novel knowledge fusion model, namely Kformer, which incorporates external knowledge through the feed-forward layer in Transformer. |
YUNZHI YAO et. al. | arxiv-cs.CL | 2022-01-14 |
| 324 | Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this research, we argue that the evidences of an answer is critical to enhancing the interpretability of QA models. |
Yuyan Chen; Yanghua Xiao; Bang Liu; | arxiv-cs.CL | 2022-01-13 |
| 325 | Towards Automated Error Analysis: Learning to Characterize Errors Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel form of meta learning that automatically learns interpretable rules that characterize the types of errors that a system makes, and demonstrate these rules’ ability to help understand and improve two NLP systems. |
Tong Gao; Shivang Singh; Raymond J. Mooney; | arxiv-cs.CL | 2022-01-13 |
| 326 | A Thousand Words Are Worth More Than A Picture: Natural Language-Centric Outside-Knowledge Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we call for a paradigm shift for the OK-VQA task, which transforms the image into plain text, so that we can enable knowledge passage retrieval, and generative question-answering in the natural language space. |
FENG GAO et. al. | arxiv-cs.CV | 2022-01-13 |
| 327 | On The Efficacy of Co-Attention Transformer Layers in Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we investigate the efficacy of co-attention transformer layers in helping the network focus on relevant regions while answering the question. |
Ankur Sikarwar; Gabriel Kreiman; | arxiv-cs.CV | 2022-01-11 |
| 328 | SCROLLS: Standardized CompaRison Over Long Language Sequences Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce SCROLLS, a suite of tasks that require reasoning over long texts. |
URI SHAHAM et. al. | arxiv-cs.CL | 2022-01-10 |
| 329 | RxWhyQA: A Clinical Question-answering Dataset with The Challenge of Multi-answer Questions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Materials and Methods We leveraged the annotated relations from the 2018 National NLP Clinical Challenges (n2c2) corpus to generate a QA dataset. |
Sungrim Moon; Huan He; Hongfang Liu; Jungwei W. Fan; | arxiv-cs.CL | 2022-01-07 |
| 330 | Does Entity Abstraction Help Generative Transformers Reason? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose and empirically explore three ways to add such abstraction: (i) as additional input embeddings, (ii) as a separate sequence to encode, and (iii) as an auxiliary prediction task for the model. |
Nicolas Gontier; Siva Reddy; Christopher Pal; | arxiv-cs.CL | 2022-01-05 |
| 331 | Multi Document Reading Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a study on Reading Comprehension and its evolution in Natural Language Processing over the past few decades. |
Avi Chawla; | arxiv-cs.CL | 2022-01-05 |
| 332 | Interactive Attention AI to Translate Low Light Photos to Captions for Night Scene Understanding in Women Safety Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: For the first time in literature, this paper develops a Deep Learning model that translates night scenes to sentences, opening new possibilities for AI applications in the safety of visually impaired women. |
Rajagopal A; Nirmala V; Arun Muthuraj Vedamanickam; | arxiv-cs.CV | 2022-01-03 |
| 333 | A Multimodal Attention Fusion Network with A Dynamic Vocabulary for TextVQA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Abstract Visual question answering (VQA) is a well-known problem in computer vision. Recently, Text-based VQA tasks are getting more and more attention because text information is … |
WU JIAJIA et. al. | Pattern Recognition | 2022-01-01 |
| 334 | Task-Oriented Multi-User Semantic Communications for VQA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Semantic communications focus on the transmission of semantic features. In this letter, we consider a task-oriented multi-user semantic communication system for multimodal data … |
Huiqiang Xie; Zhijin Qin; Geoffrey Ye Li; | IEEE Wireless Communications Letters | 2022-01-01 |
| 335 | Zero-shot Commonsense Question Answering with Cloze Translation and Consistency Optimization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we instead focus on better utilizing the \textit{implicit knowledge} stored in pre-trained language models. |
Zi-Yi Dou; Nanyun Peng; | arxiv-cs.CL | 2022-01-01 |
| 336 | Visual Question Answering By Pattern Matching and Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details |
Huayi Zhan; Peixi Xiong; Xin Wang; Xin WANG; Lan Yang; | Neurocomputing | 2022-01-01 |
| 337 | OpenQA: Hybrid QA System Relying on Structured Knowledge Base As Well As Non-structured Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose an intelligent question-answering system based on structured KB and unstructured data, called OpenQA, in which users can give query questions and the model can quickly give accurate answers back to users. |
GAOCHEN WU et. al. | arxiv-cs.CL | 2021-12-31 |
| 338 | AliMe MKG: A Multi-modal Knowledge Graph for Live-streaming E-commerce Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To enable customers to better understand a product without jumping out, we propose AliMe MKG, a multi-modal knowledge graph that aims at providing a cognitive profile for products, through which customers are able to seek information about and understand a product. |
GUOHAI XU et. al. | cikm | 2021-12-30 |
| 339 | Question Answering Using Web Lists Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe state-of-the-art methods for list extraction and ranking, that also consider the text surrounding the lists as context. |
Anoop R. Katti; Kai Hui; Adria de Gispert; Hagen Fuerstenau; | cikm | 2021-12-30 |
| 340 | FedMatch: Federated Learning Over Heterogeneous Question Answering Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to adopt federated learning for QA with the special concern on the statistical heterogeneity of the QA data. |
Jiangui Chen; Ruqing Zhang; Jiafeng Guo; Yixing Fan; Xueqi Cheng; | cikm | 2021-12-30 |
| 341 | K-AID: Enhancing Pre-trained Language Models with Domain Knowledge for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose K-AID, a systematic approach that includes a low-cost knowledge acquisition process for acquiring domain knowledge, an effective knowledge infusion module for improving model performance, and a knowledge distillation component for reducing the model size and deploying K-PLMs on resource-restricted devices (e.g., CPU) for real-world application. |
FU SUN et. al. | cikm | 2021-12-30 |
| 342 | NQuAD: 70,000+ Questions for Machine Comprehension of The Numerals in Text Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a Numeral-related Question Answering Dataset, NQuAD, for fine-grained numeracy, and propose several baselines for future works. |
Chung-Chi Chen; Hen-Hsen Huang; Hsin-Hsi Chen; | cikm | 2021-12-30 |
| 343 | Answering POI-recommendation Questions Using Tourism Reviews Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the novel and challenging task of answering Points-of-interest (POI) recommendation questions, using a collection of reviews that describe candidate answer entities (POIs). |
Danish Contractor; Krunal Shah; Aditi Partap; Parag Singla; Mausam Mausam; | cikm | 2021-12-30 |
| 344 | Automated Query Graph Generation for Querying Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to improve the overall performance of answering questions, we propose the mutual optimization technique. |
Weiguo Zheng; Mei Zhang; | cikm | 2021-12-30 |
| 345 | MVQAS: A Medical Visual Question Answering System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper demonstrates a medical visual question answering (VQA) system to address three challenges: 1) medical VQA often lacks large-scale labeled training data which requires huge efforts to build; 2) it is costly to implement and thoroughly compare medical VQA models on self-created datasets; 3) applying general VQA models to the medical domain by transfer learning is challenging due to various visual concepts between general images and medical images. |
Haoyue Bai; Xiaoyan Shan; Yefan Huang; Xiaoli Wang; | cikm | 2021-12-30 |
| 346 | Multi-Relational Graph Based Heterogeneous Multi-Task Learning in Community Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this challenge, we develop a multi-relational graph based MTL model called Heterogeneous Multi-Task Graph Isomorphism Network (HMTGIN) which efficiently solves heterogeneous CQA tasks. |
ZIZHENG LIN et. al. | cikm | 2021-12-30 |
| 347 | LiteratureQA: A Qestion Answering Corpus with Graph Knowledge on Academic Literature Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce LiteratureQA, a large question answering (QA) corpus consisting of publicly available academic papers. |
Haiwen Wang; Le Zhou; Weinan Zhang; Xinbing Wang; | cikm | 2021-12-30 |
| 348 | Tabular Data Concept Type Detection Using Star-Transformers Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on learning-based approaches for column concept type detection without relying on any metadata or queries to existing knowledge bases. |
Yiwei Zhou; Siffi Singh; Christos Christodoulopoulos; | cikm | 2021-12-30 |
| 349 | What Is Event Knowledge Graph: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper provides a comprehensive survey of EKG from history, ontology, instance, and application views. |
SAIPING GUAN et. al. | arxiv-cs.LG | 2021-12-30 |
| 350 | Complex Temporal Question Answering on Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work presents EXAQT, the first end-to-end system for answering complex temporal questions that have multiple entities and predicates, and associated temporal conditions. |
Zhen Jia; Soumajit Pramanik; Rishiraj Saha Roy; Gerhard Weikum; | cikm | 2021-12-30 |
| 351 | How to Leverage A Multi-layered Transformer Language Model for Text Clustering: An Ensemble Approach Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we present a clustering ensemble approach that harnesses all the network’s layers. |
Mira Ait-Saada; François Role; Mohamed Nadif; | cikm | 2021-12-30 |
| 352 | A Chinese Knowledge Base Question Answering System Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a HAO-Interaction question answering system, which exploits knowledge based question answering (KBQA) technology to quickly obtain an answer path for the input question, and then a creative text generation mechanism to acquire the final answer text. |
Xiaona Xue; Jinling Jiang; Wenjian Zhang; Yanxiang Huang; Xindong Wu; | cikm | 2021-12-30 |
| 353 | Question Rewriting for Open-Domain Conversational QA: Best Practices and Limitations Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we compare two types of QR approaches, generative and expansive QR, in end-to-end ODCQA systems with recently released QReCC and OR-QuAC benchmarks. |
Marco Del Tredici; Gianni Barlacchi; Xiaoyu Shen; Weiwei Cheng; Adriá de Gispert; | cikm | 2021-12-30 |
| 354 | Lightweight Visual Question Answering Using Scene Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to bridge the gap between scene graph generation and VQA by leveraging GNNs. |
SAI VIDYARANYA NUTHALAPATI et. al. | cikm | 2021-12-30 |
| 355 | VerSaChI: Finding Statistically Significant Subgraph Matches Using Chebyshev’s Inequality Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose VerSaChI for finding the top-k most similar subgraphs based on 2-hop label and structural overlap similarity with the query. |
Shubhangi Agarwal; Sourav Dutta; Arnab Bhattacharya; | cikm | 2021-12-30 |
| 356 | VisRecall: Quantifying Information Visualisation Recallability Via Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we propose a question-answering paradigm to study visualisation recallability and present VisRecall — a novel dataset consisting of 200 visualisations that are annotated with crowd-sourced human (N = 305) recallability scores obtained from 1,000 questions from five question types. |
Yao Wang; Chuhan Jiao; Mihai Bâce; Andreas Bulling; | arxiv-cs.HC | 2021-12-30 |
| 357 | Does QA-based Intermediate Training Help Fine-tuning Language Models for Text Classification? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, using the SQuAD-2.0 QA task for intermediate training for target text classification tasks, we experimented on eight tasks for single-sequence classification and eight tasks for sequence-pair classification using two base and two compact language models. |
Shiwei Zhang; Xiuzhen Zhang; | arxiv-cs.CL | 2021-12-30 |
| 358 | Pirá: A Bilingual Portuguese-English Dataset for Question-Answering About The Ocean Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents the Pirá dataset, a large set of questions and answers about the ocean and the Brazilian coast both in Portuguese and English. |
ANDRÉ F. A. PASCHOAL et. al. | cikm | 2021-12-30 |
| 359 | Towards Personalized Answer Generation in E-Commerce Via Multi-Perspective Preference Modeling Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle this challenge, we propose a novel Personalized Answer GEneration method (PAGE) with multi-perspective preference modeling, which explores historical user-generated contents to model user preference for generating personalized answers in PQA. |
Yang Deng; Yaliang Li; Wenxuan Zhang; Bolin Ding; Wai Lam; | arxiv-cs.CL | 2021-12-27 |
| 360 | Multi-Image Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an empirical study of different feature extraction methods with different loss functions. |
Harsh Raj; Janhavi Dadhania; Akhilesh Bhardwaj; Prabuchandran KJ; | arxiv-cs.CV | 2021-12-27 |
| 361 | HeteroQA: Learning Towards Question-and-Answering Through Multiple Information Sources Via Heterogeneous Graph Modeling Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Thus, we propose a question-aware heterogeneous graph transformer to incorporate the MIS in the user community to automatically generate the answer. |
SHEN GAO et. al. | arxiv-cs.CL | 2021-12-27 |
| 362 | The University of Texas at Dallas HLTRI’s Participation in EPIC-QA: Searching for Entailed Questions Revealing Novel Answer Nuggets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes our participation in both tasks of EPIC-QA, targeting: (1) Expert QA and (2) Consumer QA. |
Maxwell Weinzierl; Sanda M. Harabagiu; | arxiv-cs.CL | 2021-12-27 |
| 363 | A Survey on Non-English Question Answering Dataset Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we review question answering datasets that are available in common languages other than English such as French, German, Japanese, Chinese, Arabic, Russian, as well as the multilingual and cross-lingual question-answering datasets. |
Andreas Chandra; Affandy Fahrizain; Ibrahim; Simon Willyanto Laufried; | arxiv-cs.CL | 2021-12-27 |
| 364 | A Passage to India: Pre-trained Word Embeddings for Indian Languages Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we use various existing approaches to create multiple word embeddings for 14 Indian languages. |
Kumar Saurav; Kumar Saunack; Diptesh Kanojia; Pushpak Bhattacharyya; | arxiv-cs.CL | 2021-12-27 |
| 365 | Does CLIP Benefit Visual Question Answering in The Medical Domain As Much As It Does in The General Domain? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we present PubMedCLIP, a fine-tuned version of CLIP for the medical domain based on PubMed articles. |
Sedigheh Eslami; Gerard de Melo; Christoph Meinel; | arxiv-cs.CV | 2021-12-27 |
| 366 | New Methods & Metrics for LFQA Tasks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work addresses every one these critical bottlenecks, contributing natural language inference/generation (NLI/NLG) methods and metrics that make significant strides to their alleviation. |
Suchismit Mahapatra; Vladimir Blagojevic; Pablo Bertorello; Prasanna Kumar; | arxiv-cs.CL | 2021-12-26 |
| 367 | ArT: All-round Thinker for Unsupervised Commonsense Question-Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by human thinking experience, we propose an approach of All-round Thinker (ArT) by fully taking association during knowledge generating. |
Jiawei Wang; Hai Zhao; | arxiv-cs.CL | 2021-12-26 |
| 368 | PerCQA: Persian Community Question Answering Dataset Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present PerCQA, the first Persian dataset for CQA. |
Naghme Jamali; Yadollah Yaghoobzadeh; Hesham Faili; | arxiv-cs.CL | 2021-12-25 |
| 369 | Agent Smith: Teaching Question Answering to Jill Watson Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe Agent Smith, an interactive machine teaching agent that reduces the time taken to train a Jill for a new online class by an order of magnitude. |
Ashok Goel; Harshvardhan Sikka; Eric Gregori; | arxiv-cs.LG | 2021-12-22 |
| 370 | CLEVR3D: Compositional Language and Elementary Visual Reasoning for Question Answering in 3D Real-World Scenes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the Visual Question Answering task in 3D real-world scenes (VQA-3D), which aims to answer all possible questions given a 3D scene. |
XU YAN et. al. | arxiv-cs.CV | 2021-12-22 |
| 371 | An ASP-based Approach to Answering Natural Language Questions for Texts Literature Review Related Patents Related Grants Related Orgs Related Experts Details 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 |
| 372 | An Inference Approach To Question Answering Over Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we convert the problem of natural language querying over knowledge graphs to an inference problem over premise-hypothesis pairs. |
Aayushee Gupta; K. M. Annervaz; Ambedkar Dukkipati; Shubhashis Sengupta; | arxiv-cs.LG | 2021-12-21 |
| 373 | MuMuQA: Multimedia Multi-Hop News Question Answering Via Cross-Media Knowledge Extraction and Grounding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new QA evaluation benchmark with 1,384 questions over news articles that require cross-media grounding of objects in images onto text. |
REVANTH GANGI REDDY et. al. | arxiv-cs.CL | 2021-12-20 |
| 374 | General Greedy De-bias Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a General Greedy De-bias learning framework (GGD), which greedily trains the biased models and the base model. |
Xinzhe Han; Shuhui Wang; Chi Su; Qingming Huang; Qi Tian; | arxiv-cs.LG | 2021-12-20 |
| 375 | Cascading Adaptors to Leverage English Data to Improve Performance of Question Answering for Low-Resource Languages Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the applicability of pre-trained multilingual models to improve the performance of question answering in low-resource languages. |
Hariom A. Pandya; Bhavik Ardeshna; Dr. Brijesh S. Bhatt; | arxiv-cs.CL | 2021-12-18 |
| 376 | ActKnow: Active External Knowledge Infusion Learning for Question Answering in Low Data Regime Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a technique called ActKnow that actively infuses knowledge from Knowledge Graphs (KG) based on-demand into learning for Question Answering (QA). |
K. M. Annervaz; Pritam Kumar Nath; Ambedkar Dukkipati; | arxiv-cs.LG | 2021-12-17 |
| 377 | Reasoning Chain Based Adversarial Attack for Multi-hop Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a multi-hop reasoning chain based adversarial attack method. |
Jiayu Ding; Siyuan Wang; Qin Chen; Zhongyu Wei; | arxiv-cs.CL | 2021-12-17 |
| 378 | WebGPT: Browser-assisted Question-answering with Human Feedback IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We train and evaluate our models on ELI5, a dataset of questions asked by Reddit users. |
REIICHIRO NAKANO et. al. | arxiv-cs.CL | 2021-12-17 |
| 379 | Simple Questions Generate Named Entity Recognition Datasets Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work introduces an ask-to-generate approach, which automatically generates NER datasets by asking simple natural language questions to an open-domain question answering system (e.g., Which disease?) |
Hyunjae Kim; Jaehyo Yoo; Seunghyun Yoon; Jinhyuk Lee; Jaewoo Kang; | arxiv-cs.CL | 2021-12-16 |
| 380 | DREAM: Improving Situational QA By First Elaborating The Situation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: While we do not know how language models (LMs) answer such questions, we conjecture that they may answer more accurately if they are also provided with additional details about the question situation, elaborating the scene. To test this conjecture, we train a new model, DREAM, to answer questions that elaborate the scenes that situated questions are about, and then provide those elaborations as additional context to a question-answering (QA) model. |
Yuling Gu; Bhavana Dalvi Mishra; Peter Clark; | arxiv-cs.CL | 2021-12-16 |
| 381 | Models in The Loop: Aiding Crowdworkers with Generative Annotation Assistants Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we examine whether we can maintain the advantages of DADC, without incurring the additional cost. |
MAX BARTOLO et. al. | arxiv-cs.CL | 2021-12-16 |
| 382 | Long Context Question Answering Via Supervised Contrastive Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel method for equipping long-context QA models with an additional sequence-level objective for better identification of the supporting evidence. |
Avi Caciularu; Ido Dagan; Jacob Goldberger; Arman Cohan; | arxiv-cs.CL | 2021-12-16 |
| 383 | Distilled Dual-Encoder Model for Vision-Language Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a cross-modal attention distillation framework to train a dual-encoder model for vision-language understanding tasks, such as visual reasoning and visual question answering. |
ZEKUN WANG et. al. | arxiv-cs.CL | 2021-12-16 |
| 384 | Nirikshak: An Autonomous Testing Framework Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This project is an effort to make such a framework. |
Yash Mahalwal; Pawel Pratyush; Yogesh Poonia; | arxiv-cs.SE | 2021-12-15 |
| 385 | QuALITY: Question Answering with Long Input Texts, Yes! Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To enable building and testing models on long-document comprehension, we introduce QuALITY, a multiple-choice QA dataset with context passages in English that have an average length of about 5,000 tokens, much longer than typical current models can process. |
RICHARD YUANZHE PANG et. al. | arxiv-cs.CL | 2021-12-15 |
| 386 | 3D Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the first attempt at extending VQA to the 3D domain, which can facilitate artificial intelligence’s perception of 3D real-world scenarios. |
Shuquan Ye; Dongdong Chen; Songfang Han; Jing Liao; | arxiv-cs.CV | 2021-12-15 |
| 387 | LongT5: Efficient Text-To-Text Transformer for Long Sequences Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a new model, called LongT5, with which we explore the effects of scaling both the input length and model size at the same time. |
MANDY GUO et. al. | arxiv-cs.CL | 2021-12-15 |
| 388 | QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details 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 |
| 389 | CONQRR: Conversational Query Rewriting for Retrieval with Reinforcement Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To facilitate their use, we develop a query rewriting model CONQRR that rewrites a conversational question in the context into a standalone question. |
ZEQIU WU et. al. | arxiv-cs.CL | 2021-12-15 |
| 390 | Learning Rich Representation of Keyphrases from Text Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we explore how to learn 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 |
| 391 | Block-Skim: Efficient Question Answering for Transformer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: However, different from other tasks such as sequence classification, answering the raised question does not necessarily need all the tokens in the context paragraph. Following this motivation, we propose Block-skim, which learns to skim unnecessary context in higher hidden layers to improve and accelerate the Transformer performance. |
YUE GUAN et. al. | arxiv-cs.CL | 2021-12-15 |
| 392 | Learning to Retrieve Passages Without Supervision Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Dense retrievers for open-domain question answering (ODQA) have been shown to achieve impressive performance by training on large datasets of question-passage pairs. In this work we ask whether this dependence on labeled data can be reduced via unsupervised pretraining that is geared towards ODQA. |
Ori Ram; Gal Shachaf; Omer Levy; Jonathan Berant; Amir Globerson; | arxiv-cs.CL | 2021-12-14 |
| 393 | Learning to Transpile AMR Into SPARQL Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a transition-based system to transpile Abstract Meaning Representation (AMR) into SPARQL for Knowledge Base Question Answering (KBQA). |
MIHAELA BORNEA et. al. | arxiv-cs.CL | 2021-12-14 |
| 394 | Scaling Up Query-Focused Summarization to Meet Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, we show how to extend this task to make it more realistic. |
Weijia Zhang; Svitlana Vakulenko; Thilina Rajapakse; Evangelos Kanoulas; | arxiv-cs.CL | 2021-12-14 |
| 395 | You Only Need One Model for Open-domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose casting the retriever and the reranker as hard-attention mechanisms applied sequentially within the transformer architecture and feeding the resulting computed representations to the reader. |
HAEJUN LEE et. al. | arxiv-cs.CL | 2021-12-14 |
| 396 | Multi-Instance Training for Question Answering Across Table and Linked Text Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Answering natural language questions using information from tables (TableQA) is of considerable recent interest. In many applications, tables occur not in isolation, but embedded … |
VISHWAJEET KUMAR et. al. | arxiv-cs.CL | 2021-12-14 |
| 397 | Bilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on these two problems and propose a Graph Matching Attention (GMA) network. |
JianJian Cao; Xiameng Qin; Sanyuan Zhao; Jianbing Shen; | arxiv-cs.CV | 2021-12-14 |
| 398 | Do Answers to Boolean Questions Need Explanations? Yes Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We confirm our findings with a user study which shows that our extracted evidence spans enhance the user experience. |
Sara Rosenthal; Mihaela Bornea; Avirup Sil; Radu Florian; Scott McCarley; | arxiv-cs.CL | 2021-12-14 |
| 399 | Improving and Diagnosing Knowledge-Based Visual Question Answering Via Entity Enhanced Knowledge Injection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we empirically study how and whether such methods, applied in a bi-modal setting, can improve an existing VQA system’s performance on the KBVQA task. |
Diego Garcia-Olano; Yasumasa Onoe; Joydeep Ghosh; | arxiv-cs.CL | 2021-12-13 |
| 400 | Few-shot Multi-hop Question Answering Over Knowledge Base Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose an efficient pipeline method equipped with a pre-trained language model. |
Meihao Fan; Lei Zhang; Siyao Xiao; Yuru Liang; | arxiv-cs.CL | 2021-12-13 |
| 401 | Explanation Container in Case-Based Biomedical Question-Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present the design of the Explanatory Agent (xARA), a case-based ARA that answers biomedical queries by accessing multiple KPs, ranking results, and explaining the ranking of results. |
Prateek Goel; Adam J. Johs; Manil Shrestha; Rosina O. Weber; | arxiv-cs.AI | 2021-12-13 |
| 402 | Video As Conditional Graph Hierarchy for Multi-Granular Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To align with the multi-granular essence of linguistic concepts in language queries, we propose to model video as a conditional graph hierarchy which weaves together visual facts of different granularity in a level-wise manner, with the guidance of corresponding textual cues. |
JUNBIN XIAO et. al. | arxiv-cs.CV | 2021-12-12 |
| 403 | Change Detection Meets Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to provide every user with flexible access to change information and help them better understand land-cover changes, we introduce a novel task: change detection-based visual question answering (CDVQA) on multi-temporal aerial images. |
Zhenghang Yuan; Lichao Mou; Zhitong Xiong; Xiaoxiang Zhu; | arxiv-cs.CV | 2021-12-12 |
| 404 | Injecting Numerical Reasoning Skills Into Knowledge Base Question Answering Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a new embedding-based KBQA framework which particularly takes numerical reasoning into account. |
YU FENG et. al. | arxiv-cs.CL | 2021-12-11 |
| 405 | TempoQR: Temporal Question Reasoning Over Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Existing solutions are mainly designed for simple temporal questions that can be answered directly by a single TKG fact. |
COSTAS MAVROMATIS et. al. | arxiv-cs.CL | 2021-12-10 |
| 406 | Improving The Question Answering Quality Using Answer Candidate Filtering Based on Natural-Language Features Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our main contribution is an approach capable of identifying wrong answers provided by a QA system. |
Aleksandr Gashkov; Aleksandr Perevalov; Maria Eltsova; Andreas Both; | arxiv-cs.IR | 2021-12-10 |
| 407 | Improving Language Models By Retrieving from Trillions of Tokens IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We enhance auto-regressive language models by conditioning on document chunks retrieved from a large corpus, based on local similarity with preceding tokens. |
SEBASTIAN BORGEAUD et. al. | arxiv-cs.CL | 2021-12-08 |
| 408 | Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matrices Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this review work, the research directions of QA field are analyzed based on the type of question, answer type, source of evidence-answer, and modeling approach. |
Hariom A. Pandya; Brijesh S. Bhatt; | arxiv-cs.CL | 2021-12-07 |
| 409 | Qualitative Analysis for Human Centered AI Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this article, we argue that qualitative analysis (QA) can be a valuable tool in this process, supplementing, informing, and extending the possibilities of AI models. |
Orestis Papakyriakopoulos; Elizabeth Anne Watkins; Amy Winecoff; Klaudia Jaźwińska; Tithi Chattopadhyay; | arxiv-cs.HC | 2021-12-07 |
| 410 | Semantic Answer Type and Relation Prediction Task (SMART 2021) Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Each year the International Semantic Web Conference organizes a set of Semantic Web Challenges to establish competitions that will advance state-of-the-art solutions in some problem domains. |
NANDANA MIHINDUKULASOORIYA et. al. | arxiv-cs.CL | 2021-12-07 |
| 411 | Natural Answer Generation: From Factoid Answer to Full-length Answer Using Grammar Correction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposes a system that outputs a full-length answer given a question and the extracted factoid answer (short spans such as named entities) as the input. |
Manas Jain; Sriparna Saha; Pushpak Bhattacharyya; Gladvin Chinnadurai; Manish Kumar Vatsa; | arxiv-cs.CL | 2021-12-07 |
| 412 | Automated Story Generation As Question-Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel approach to automated story generation that treats the problem as one of generative question-answering. |
Louis Castricato; Spencer Frazier; Jonathan Balloch; Nitya Tarakad; Mark Riedl; | arxiv-cs.CL | 2021-12-07 |
| 413 | MoCA: Incorporating Multi-stage Domain Pretraining and Cross-guided Multimodal Attention for Textbook Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To tackle the above issues, we propose a novel model named MoCA, which incorporates multi-stage domain pretraining and multimodal cross attention for the TQA task. |
FANGZHI XU et. al. | arxiv-cs.MM | 2021-12-06 |
| 414 | JointLK: Joint Reasoning with Language Models and Knowledge Graphs for Commonsense Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel model, JointLK, which solves the above limitations through the joint reasoning of LM and GNN and the dynamic KGs pruning mechanism. |
Yueqing Sun; Qi Shi; Le Qi; Yu Zhang; | arxiv-cs.CL | 2021-12-05 |
| 415 | A Russian Jeopardy! Data Set for Question-Answering Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: It is also a challenging task that attracted the attention of a very general audience at the quiz show Jeopardy! In this article we describe a Jeopardy!-like Russian QA data set collected from the official Russian quiz database Chgk (che ge ka). |
Elena Mikhalkova; | arxiv-cs.CL | 2021-12-04 |
| 416 | Multitask Finetuning for Improving Neural Machine Translation in Indian Languages Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a Multitask Finetuning methodology which combines the Bilingual Machine Translation task with an auxiliary Causal Language Modeling task to improve performance on the former task on Indian Languages. |
Shaily Desai; Atharva Kshirsagar; Manisha Marathe; | arxiv-cs.CL | 2021-12-03 |
| 417 | MetaQA: Combining Expert Agents for Multi-Skill Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to combine expert agents with a novel, flexible, and training-efficient architecture that considers questions, answer predictions, and answer-prediction confidence scores to select the best answer among a list of answer candidates. |
Haritz Puerto; Gözde Gül Şahin; Iryna Gurevych; | arxiv-cs.CL | 2021-12-03 |
| 418 | Classification-Regression for Chart Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: Charts are a popular and effective form of data visualization. Chart question answering (CQA) is a task used for assessing chart comprehension, which is fundamentally different … |
Matan Levy; Rami Ben-Ari; Dani Lischinski; | arxiv-cs.CV | 2021-11-29 |
| 419 | Action Based Network for Conversation Question Reformulation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an action-based approach to recover the complete expression of the question. |
Zheyu Ye; Jiangning Liu; Qian Yu; Jianxun Ju; | arxiv-cs.CL | 2021-11-29 |
| 420 | LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a Lightweight Visual-Linguistic Reasoning framework named LiVLR. |
Jingjing Jiang; Ziyi Liu; Nanning Zheng; | arxiv-cs.CV | 2021-11-29 |
| 421 | AssistSR: Task-oriented Question-driven Video Segment Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In contrast, we present a new task called Task-oriented Question-driven Video Segment Retrieval (TQVSR). |
Stan Weixian Lei; Yuxuan Wang; Dongxing Mao; Difei Gao; Mike Zheng Shou; | arxiv-cs.CV | 2021-11-29 |
| 422 | A Grounded Well-being Conversational Agent with Multiple Interaction Modes: Preliminary Results Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we seek to address this limitation via a conversational agent that adopts one aspect of in-person doctor-patient interactions: A human avatar to facilitate medical grounded question answering. |
Xinxin Yan; Ndapa Nakashole; | arxiv-cs.CL | 2021-11-28 |
| 423 | Tapping BERT for Preposition Sense Disambiguation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel methodology for preposition sense disambiguation (PSD), which does not use any linguistic tools. |
Siddhesh Pawar; Shyam Thombre; Anirudh Mittal; Girishkumar Ponkiya; Pushpak Bhattacharyya; | arxiv-cs.CL | 2021-11-27 |
| 424 | Answer Generation for Questions With Multiple Information Sources in E-Commerce Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Through this work we propose a novel pipeline (MSQAP) that utilizes the rich information present in the aforementioned sources by separately performing relevancy and ambiguity prediction before generating a response. |
Anand A. Rajasekar; Nikesh Garera; | arxiv-cs.CL | 2021-11-27 |
| 425 | Scene Graph Generation with Geometric Context Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduced a post-processing algorithm called Geometric Context to understand the visual scenes better geometrically. |
Vishal Kumar; Albert Mundu; Satish Kumar Singh; | arxiv-cs.CV | 2021-11-25 |
| 426 | Zero-Shot Open-Book Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This article proposes a solution for answering natural language questions from a corpus of Amazon Web Services (AWS) technical documents with no domain-specific labeled data (zero-shot). |
Sia Gholami; Mehdi Noori; | arxiv-cs.CL | 2021-11-22 |
| 427 | Many Heads But One Brain: An Overview of Fusion Brain Challenge on AI Journey 2021 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Supporting the current trend in the AI community, we propose the AI Journey 2021 Challenge called Fusion Brain which is targeted to make the universal architecture process different modalities (namely, images, texts, and code) and to solve multiple tasks for vision and language. |
DARIA BAKSHANDAEVA et. al. | arxiv-cs.CV | 2021-11-21 |
| 428 | Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Scallop, a system that builds upon probabilistic deductive databases, to bridge this gap. |
JIANI HUANG et. al. | nips | 2021-11-20 |
| 429 | Textbook to Triples: Creating Knowledge Graph in The Form of Triples from AI TextBook Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, an effort has been made towards developing a system that could convert the text from a given textbook into triples that can be used to visualize as a knowledge graph and use for further applications. |
Aman Kumar; Swathi Dinakaran; | arxiv-cs.CL | 2021-11-20 |
| 430 | Human-Adversarial Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to stress test VQA models, we benchmark them against human-adversarial examples. |
SASHA SHENG et. al. | nips | 2021-11-20 |
| 431 | SQALER: Scaling Question Answering By Decoupling Multi-Hop and Logical Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we address this issue by showing that multi-hop and more complex logical reasoning can be accomplished separately without losing expressive power. |
Mattia Atzeni; Jasmina Bogojeska; Andreas Loukas; | nips | 2021-11-20 |
| 432 | Vector-valued Distance and Gyrocalculus on The Space of Symmetric Positive Definite Matrices Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the use of the vector-valued distance to compute distances and extract geometric information from the manifold of symmetric positive definite matrices (SPD), and develop gyrovector calculus, constructing analogs of vector space operations in this curved space. |
Federico Lopez; Beatrice Pozzetti; Steve Trettel; Michael Strube; Anna Wienhard; | nips | 2021-11-20 |
| 433 | One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Cross-lingual Open-Retrieval Answer Generation (CORA), the first unified many-to-many question answering (QA) model that can answer questions across many languages, even for ones without language-specific annotated data or knowledge sources. |
Akari Asai; Xinyan Yu; Jungo Kasai; Hanna Hajishirzi; | nips | 2021-11-20 |
| 434 | Introspective Distillation for Robust Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel debiasing method called Introspective Distillation (IntroD) to make the best of both worlds for QA. |
Yulei Niu; Hanwang Zhang; | nips | 2021-11-20 |
| 435 | End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an end-to-end differentiable training method for retrieval-augmented open-domain question answering systems that combine information from multiple retrieved documents when generating answers. |
Devendra Singh; Siva Reddy; Will Hamilton; Chris Dyer; Dani Yogatama; | nips | 2021-11-20 |
| 436 | Debiased Visual Question Answering from Feature and Sample Perspectives Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a method named D-VQA to alleviate the above challenges from the feature and sample perspectives. |
Zhiquan Wen; Guanghui Xu; Mingkui Tan; Qingyao Wu; Qi Wu; | nips | 2021-11-20 |
| 437 | How Modular Should Neural Module Networks Be for Systematic Generalization? Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we demonstrate that the degree of modularity of the NMN have large influence on systematic generalization. |
Vanessa D'Amario; Tomotake Sasaki; Xavier Boix; | nips | 2021-11-20 |
| 438 | Learning from Inside: Self-driven Siamese Sampling and Reasoning for Video Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To consider the interdependent knowledge between contextual clips into the network inference, we propose a Siamese Sampling and Reasoning (SiaSamRea) approach, which consists of a siamese sampling mechanism to generate sparse and similar clips (i.e., siamese clips) from the same video, and a novel reasoning strategy for integrating the interdependent knowledge between contextual clips into the network. |
WEIJIANG YU et. al. | nips | 2021-11-20 |
| 439 | Medical Visual Question Answering: A Survey Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is to provide comprehensive information for researchers interested in medical artificial intelligence. |
ZHIHONG LIN et. al. | arxiv-cs.CV | 2021-11-19 |
| 440 | Building A Question Answering System for The Manufacturing Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To solve the problem of insufficient training data for the technology question answering system, we propose a method to generate questions according to a declarative sentence from several different dimensions so that multiple question-answer pairs can be obtained from a declarative sentence. |
LIU XINGGUANG et. al. | arxiv-cs.CL | 2021-11-18 |
| 441 | UFO: A UniFied TransfOrmer for Vision-Language Representation Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a single UniFied transfOrmer (UFO), which is capable of processing either unimodal inputs (e.g., image or language) or multimodal inputs (e.g., the concatenation of the image and the question), for vision-language (VL) representation learning. |
JIANFENG WANG et. al. | arxiv-cs.CV | 2021-11-18 |
| 442 | Triple Attention Network Architecture for MovieQA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel network with triple-attention architecture for the inclusion of audio in the Movie QA task. |
Ankit Shah; Tzu-Hsiang Lin; Shijie Wu; | arxiv-cs.MM | 2021-11-18 |
| 443 | Document AI: Benchmarks, Models and Applications Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Document AI, or Document Intelligence, is a relatively new research topic that refers to the techniques for automatically reading, understanding, and analyzing business documents. |
Lei Cui; Yiheng Xu; Tengchao Lv; Furu Wei; | arxiv-cs.CL | 2021-11-16 |
| 444 | Language Bias in Visual Question Answering: A Survey and Taxonomy Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we conduct a comprehensive review and analysis of this field for the first time, and classify the existing methods according to three categories, including enhancing visual information, weakening language priors, data enhancement and training strategies. |
Desen Yuan; | arxiv-cs.CV | 2021-11-16 |
| 445 | QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a QA-based framework for PRF called QA4PRF to utilize contextual information in documents. |
HANDONG MA et. al. | arxiv-cs.IR | 2021-11-16 |
| 446 | Achieving Human Parity on Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes our recent research of AliceMind-MMU (ALIbaba’s Collection of Encoder-decoders from Machine IntelligeNce lab of Damo academy – MultiMedia Understanding) that obtains similar or even slightly better results than human being does on VQA. |
MING YAN et. al. | arxiv-cs.CL | 2021-11-16 |
| 447 | Question-Based Salient Span Selection for More Controllable Text Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details 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 |
| 448 | Calculating Question Similarity Is Enough: A New Method for KBQA Tasks Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this kind of pipeline methods, errors in any procedure will inevitably propagate to the final prediction. To address this challenge, this paper proposes a Corpus Generation – Retrieve Method (CGRM) with Pre-training Language Model (PLM) for the KBQA task. |
HANYU ZHAO et. al. | arxiv-cs.CL | 2021-11-15 |
| 449 | Graph Relation Transformer: Incorporating Pairwise Object Features Into The Transformer Architecture Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to overcome these shortcomings, we propose a Graph Relation Transformer (GRT), which uses edge information in addition to node information for graph attention computation in the Transformer. |
Michael Yang; Aditya Anantharaman; Zachary Kitowski; Derik Clive Robert; | arxiv-cs.CV | 2021-11-11 |
| 450 | A Chinese Multi-type Complex Questions Answering Dataset Over Wikidata Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Together with the dataset, we present a text-to-SPARQL baseline model, which can effectively answer multi-type complex questions, such as factual questions, dual intent questions, boolean questions, and counting questions, with Wikidata as the background knowledge. |
JIANYUN ZOU et. al. | arxiv-cs.CL | 2021-11-11 |
| 451 | Automated Question Generation and Question Answering from Turkish Texts Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we fine-tune a multilingual T5 (mT5) transformer in a multi-task setting for QA, QG and answer extraction tasks using Turkish QA datasets. |
Fatih Cagatay Akyon; Devrim Cavusoglu; Cemil Cengiz; Sinan Onur Altinuc; Alptekin Temizel; | arxiv-cs.LG | 2021-11-11 |
| 452 | AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our pipeline gathers annotations for all subtasks of answer summarization, including relevant answer sentence selection, grouping these sentences based on perspectives, summarizing each perspective, and producing an overall summary. We analyze and benchmark state-of-the-art models on these subtasks and introduce a novel unsupervised approach for multi-perspective data augmentation that boosts summarization performance according to automatic evaluation. |
Alexander R. Fabbri; Xiaojian Wu; Srini Iyer; Haoran Li; Mona Diab; | arxiv-cs.CL | 2021-11-11 |
| 453 | Cross-lingual Adaption Model-Agnostic Meta-Learning for Natural Language Understanding Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose XLA-MAML, which performs direct cross-lingual adaption in the meta-learning stage. |
Qianying Liu; Fei Cheng; Sadao Kurohashi; | arxiv-cs.CL | 2021-11-10 |
| 454 | Recent Advances in Automated Question Answering In Biomedical Domain Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the basic methodologies used for developing general domain QA systems, followed by a thorough investigation of different aspects of biomedical QA systems, including benchmark datasets and several proposed approaches, both using structured databases and collection of texts. |
Krishanu Das Baksi; | arxiv-cs.AI | 2021-11-10 |
| 455 | Pre-trained Transformer-Based Approach for Arabic Question Answering : A Comparative Study Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we evaluate the state-of-the-art pre-trained transformers models for Arabic QA using four reading comprehension datasets which are Arabic-SQuAD, ARCD, AQAD, and TyDiQA-GoldP datasets. |
Kholoud Alsubhi; Amani Jamal; Areej Alhothali; | arxiv-cs.CL | 2021-11-10 |
| 456 | A Two-Stage Approach Towards Generalization in Knowledge Base Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To achieve this generalization, we introduce a KBQA framework based on a 2-stage architecture that explicitly separates semantic parsing from the knowledge base interaction, facilitating transfer learning across datasets and knowledge graphs. |
SRINIVAS RAVISHANKAR et. al. | arxiv-cs.CL | 2021-11-10 |
| 457 | Visual Question Answering Based on Formal Logic Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a formal logic framework where (i) images are converted to logical background facts with the help of scene graphs, (ii) the questions are translated to first-order predicate logic clauses using a transformer based deep learning model, and (iii) perform satisfiability checks, by using the background knowledge and the grounding of predicate clauses, to obtain the answer. |
Muralikrishnna G. Sethuraman; Ali Payani; Faramarz Fekri; J. Clayton Kerce; | arxiv-cs.CV | 2021-11-08 |
| 458 | Ontology-based Question Answering Over Corporate Structured Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We describe the dialogue engine for a chat bot which can keep the conversation context and ask clarifying questions, simulating some aspects of the human logical thinking. |
Sergey Gorshkov; Constantin Kondratiev; Roman Shebalov; | arxiv-cs.SE | 2021-11-08 |
| 459 | Transformer Based Bengali Chatbot Using General Knowledge Dataset Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this research, we applied the transformer model for Bengali general knowledge chatbot based on the Bengali general knowledge Question Answer (QA) dataset. |
Abu Kaisar Mohammad Masum; Sheikh Abujar; Sharmin Akter; Nushrat Jahan Ria; Syed Akhter Hossain; | arxiv-cs.CL | 2021-11-06 |
| 460 | ReasonBERT: Pre-trained to Reason with Distant Supervision Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present ReasonBert, a pre-training method that augments language models with the ability to reason over long-range relations and multiple, possibly hybrid contexts. |
XIANG DENG et. al. | emnlp | 2021-11-05 |
| 461 | Structured Context and High-Coverage Grammar for Conversational Question Answering Over Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a new Logical Form (LF) grammar that can model a wide range of queries on the graph while remaining sufficiently simple to generate supervision data efficiently. |
Pierre Marion; Pawel Nowak; Francesco Piccinno; | emnlp | 2021-11-05 |
| 462 | Powering Comparative Classification with Sentiment Analysis Via Domain Adaptive Knowledge Transfer Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Sentiment Analysis Enhanced COmparative Network (SAECON) which improves CPC accuracy with a sentiment analyzer that learns sentiments to individual entities via domain adaptive knowledge transfer. |
Zeyu Li; Yilong Qin; Zihan Liu; Wei Wang; | emnlp | 2021-11-05 |
| 463 | Q2: Evaluating Factual Consistency in Knowledge-Grounded Dialogues Via Question Generation and Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details 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 |
| 464 | Simple and Effective Unsupervised Redundancy Elimination to Compress Dense Vectors for Passage Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we analyze the redundancy present in encoded dense vectors and show that the default dimension of 768 is unnecessarily large. |
Xueguang Ma; Minghan Li; Kai Sun; Ji Xin; Jimmy Lin; | emnlp | 2021-11-05 |
| 465 | ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization Literature Review Related Patents Related Grants Related Orgs Related Experts Details 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 |
| 466 | TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering Over Relation Graph IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose TransferNet, an effective and transparent model for multi-hop QA, which supports both label and text relations in a unified framework. |
Jiaxin Shi; Shulin Cao; Lei Hou; Juanzi Li; Hanwang Zhang; | emnlp | 2021-11-05 |
| 467 | Refocusing on Relevance: Personalization in NLG Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we argue that NLG systems in general should place a much higher level of emphasis on making use of additional context, and suggest that relevance (as used in Information Retrieval) be thought of as a crucial tool for designing user-oriented text-generating tasks. |
Shiran Dudy; Steven Bedrick; Bonnie Webber; | emnlp | 2021-11-05 |
| 468 | Improving Query Graph Generation for Complex Question Answering Over Knowledge Base Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new solution to query graph generation that works in the opposite manner: we start with the entire knowledge base and gradually shrink it to the desired query graph. |
Kechen Qin; Cheng Li; Virgil Pavlu; Javed Aslam; | emnlp | 2021-11-05 |
| 469 | Adaptive Information Seeking for Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel adaptive information-seeking strategy for open-domain question answering, namely AISO. |
Yunchang Zhu; Liang Pang; Yanyan Lan; Huawei Shen; Xueqi Cheng; | emnlp | 2021-11-05 |
| 470 | Phrase Retrieval Learns Passage Retrieval, Too Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we follow the intuition that retrieving phrases naturally entails retrieving larger text blocks and study whether phrase retrieval can serve as the basis for coarse-level retrieval including passages and documents. |
Jinhyuk Lee; Alexander Wettig; Danqi Chen; | emnlp | 2021-11-05 |
| 471 | SituatedQA: Incorporating Extra-Linguistic Contexts Into QA IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To study this challenge, we introduce SituatedQA, an open-retrieval QA dataset where systems must produce the correct answer to a question given the temporal or geographical context. |
Michael Zhang; Eunsol Choi; | emnlp | 2021-11-05 |
| 472 | ECONET: Effective Continual Pretraining of Language Models for Event Temporal Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a continual pre-training approach that equips PTLMs with targeted knowledge about event temporal relations. |
Rujun Han; Xiang Ren; Nanyun Peng; | emnlp | 2021-11-05 |
| 473 | Paired Examples As Indirect Supervision in Latent Decision Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we introduce a way to leverage paired examples that provide stronger cues for learning latent decisions. |
Nitish Gupta; Sameer Singh; Matt Gardner; Dan Roth; | emnlp | 2021-11-05 |
| 474 | Improving Unsupervised Question Answering Via Summarization-Informed Question Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In order to overcome these shortcomings, we propose a distantly-supervised QG method which uses questions generated heuristically from summaries as a source of training data for a QG system. |
CHENYANG LYU et. al. | emnlp | 2021-11-05 |
| 475 | Large-Scale Relation Learning for Question Answering Over Knowledge Bases with Pre-trained Language Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To bridge the gap between the natural language and the structured KB, we propose three relation learning tasks for BERT-based KBQA, including relation extraction, relation matching, and relation reasoning. |
YUANMENG YAN et. al. | emnlp | 2021-11-05 |
| 476 | Grounded Graph Decoding Improves Compositional Generalization in Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Grounded Graph Decoding, a method to improve compositional generalization of language representations by grounding structured predictions with an attention mechanism. |
YU GAI et. al. | arxiv-cs.CL | 2021-11-05 |
| 477 | Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering Without Evidence Annotation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a novel approach (DistDR) that iteratively improves over a weak retriever by alternately finding evidence from the up-to-date model and encouraging the model to learn the most likely evidence. |
Chen Zhao; Chenyan Xiong; Jordan Boyd-Graber; Hal Daum? III; | emnlp | 2021-11-05 |
| 478 | Broaden The Vision: Geo-Diverse Visual Commonsense Reasoning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we construct a Geo-Diverse Visual Commonsense Reasoning dataset (GD-VCR) to test vision-and-language models’ ability to understand cultural and geo-location-specific commonsense. |
Da Yin; Liunian Harold Li; Ziniu Hu; Nanyun Peng; Kai-Wei Chang; | emnlp | 2021-11-05 |
| 479 | MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we improve multilingual text-to-text transfer Transformer with translation pairs (mT6). |
ZEWEN CHI et. al. | emnlp | 2021-11-05 |
| 480 | Case-based Reasoning for Natural Language Queries Over Knowledge Bases IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a neuro-symbolic CBR approach (CBR-KBQA) for question answering over large knowledge bases. |
RAJARSHI DAS et. al. | emnlp | 2021-11-05 |
| 481 | What’s in A Name? Answer Equivalence For Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This work explores mining alias entities from knowledge bases and using them as additional gold answers (i.e., equivalent answers). |
Chenglei Si; Chen Zhao; Jordan Boyd-Graber; | emnlp | 2021-11-05 |
| 482 | Editing Factual Knowledge in Language Models IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present KnowledgeEditor, a method which can be used to edit this knowledge and, thus, fix ‘bugs’ or unexpected predictions without the need for expensive re-training or fine-tuning. |
Nicola De Cao; Wilker Aziz; Ivan Titov; | emnlp | 2021-11-05 |
| 483 | What’s in Your Head? Emergent Behaviour in Multi-Task Transformer Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we examine the behaviour of non-target heads, that is, the output of heads when given input that belongs to a different task than the one they were trained for. |
Mor Geva; Uri Katz; Aviv Ben-Arie; Jonathan Berant; | emnlp | 2021-11-05 |
| 484 | Will This Question Be Answered? Question Filtering Via Answer Model Distillation for Efficient Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a novel approach towards improving the efficiency of Question Answering (QA) systems by filtering out questions that will not be answered by them. |
Siddhant Garg; Alessandro Moschitti; | emnlp | 2021-11-05 |
| 485 | Zero-Shot Dialogue State Tracking Via Cross-Task Transfer IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose to transfer the cross-task knowledge from general question answering (QA) corpora for the zero-shot DST task. |
ZHAOJIANG LIN et. al. | emnlp | 2021-11-05 |
| 486 | Topic Transferable Table Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we simulate the practical topic shift scenario by designing novel challenge benchmarks WikiSQL-TS and WikiTable-TS, consisting of train-dev-test splits in five distinct topic groups, based on the popular WikiSQL and WikiTable-Questions datasets. |
SANEEM CHEMMENGATH et. al. | emnlp | 2021-11-05 |
| 487 | Evaluation Paradigms in Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Question answering (QA) primarily descends from two branches of research: (1) Alan Turing’s investigation of machine intelligence at Manchester University and (2) Cyril Cleverdon’s comparison of library card catalog indices at Cranfield University. This position paper names and distinguishes these paradigms. |
Pedro Rodriguez; Jordan Boyd-Graber; | emnlp | 2021-11-05 |
| 488 | HittER: Hierarchical Transformers for Knowledge Graph Embeddings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose HittER, a Hierarchical Transformer model to jointly learn Entity-relation composition and Relational contextualization based on a source entity’s neighborhood. |
SANXING CHEN et. al. | emnlp | 2021-11-05 |
| 489 | Perhaps PTLMs Should Go to School – A Task to Assess Open Book and Closed Book QA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal is to deliver a new task and leaderboard to stimulate research on question answering and pre-trained language models (PTLMs) to understand a significant instructional document, e.g., an introductory college textbook or a manual. |
MANUEL CIOSICI et. al. | emnlp | 2021-11-05 |
| 490 | Enhanced Language Representation with Label Knowledge for Span Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address those problems, we introduce a fresh paradigm to integrate label knowledge and further propose a novel model to explicitly and efficiently integrate label knowledge into text representations. |
Pan Yang; Xin Cong; Zhenyu Sun; Xingwu Liu; | emnlp | 2021-11-05 |
| 491 | MLEC-QA: A Chinese Multi-Choice Biomedical Question Answering Dataset Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present MLEC-QA, the largest-scale Chinese multi-choice biomedical QA dataset, collected from the National Medical Licensing Examination in China. |
Jing Li; Shangping Zhong; Kaizhi Chen; | emnlp | 2021-11-05 |
| 492 | Cross-Policy Compliance Detection Via Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose to address policy compliance detection via decomposing it into question answering, where questions check whether the conditions stated in the policy apply to the scenario, and an expression tree combines the answers to obtain the label. |
Marzieh Saeidi; Majid Yazdani; Andreas Vlachos; | emnlp | 2021-11-05 |
| 493 | QuestEval: Summarization Asks for Fact-based Evaluation IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we extend previous approaches and propose a unified framework, named QuestEval. |
THOMAS SCIALOM et. al. | emnlp | 2021-11-05 |
| 494 | Generating Self-Contained and Summary-Centric Question Answer Pairs Via Differentiable Reward Imitation Learning Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by suggested question generation in conversational news recommendation systems, we propose a model for generating question-answer pairs (QA pairs) with self-contained, summary-centric questions and length-constrained, article-summarizing answers. |
Li Zhou; Kevin Small; Yong Zhang; Sandeep Atluri; | emnlp | 2021-11-05 |
| 495 | Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a method to improve the Cross-lingual Question Answering performance without requiring additional annotated data, leveraging Question Generation models to produce synthetic samples in a cross-lingual fashion. |
ARIJ RIABI et. al. | emnlp | 2021-11-05 |
| 496 | QA-Align: Representing Cross-Text Content Overlap By Aligning Question-Answer Propositions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We employ crowd-workers for constructing a dataset of QA-based alignments, and present a baseline QA alignment model trained over our dataset. |
Daniela Brook Weiss; Paul Roit; Ayal Klein; Ori Ernst; Ido Dagan; | emnlp | 2021-11-05 |
| 497 | Incorporating Medical Knowledge in BERT for Clinical Relation Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To solve these issues, in this research, we conduct a comprehensive examination of different techniques to add medical knowledge into a pre-trained BERT model for clinical relation extraction. |
Arpita Roy; Shimei Pan; | emnlp | 2021-11-05 |
| 498 | Measuring Association Between Labels and Free-Text Rationales IF:3 Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the extent to which the labels and rationales predicted by these models are associated, a necessary property of faithful explanation. |
Sarah Wiegreffe; Ana Marasovic; Noah A. Smith; | emnlp | 2021-11-05 |
| 499 | Generative Context Pair Selection for Multi-hop Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a generative context selection model for multi-hop QA that reasons about how the given question could have been generated given a context pair and not just independent contexts. |
DHEERU DUA et. al. | emnlp | 2021-11-05 |
| 500 | Multivalent Entailment Graphs for Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We make three contributions: (1) we reinterpret the Distributional Inclusion Hypothesis to model entailment between predicates of different valencies, like DEFEAT(Biden, Trump) entails WIN(Biden); (2) we actualize this theory by learning unsupervised Multivalent Entailment Graphs of open-domain predicates; and (3) we demonstrate the capabilities of these graphs on a novel question answering task. |
NICK MCKENNA et. al. | emnlp | 2021-11-05 |
| 501 | End-to-End Entity Resolution and Question Answering Using Differentiable Knowledge Graphs Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we extend the boundaries of E2E learning for KGQA to include the training of an ER component. |
Amir Saffari; Armin Oliya; Priyanka Sen; Tom Ayoola; | emnlp | 2021-11-05 |
| 502 | Foreseeing The Benefits of Incidental Supervision Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a unified PAC-Bayesian motivated informativeness measure, PABI, that characterizes the uncertainty reduction provided by incidental supervision signals. |
Hangfeng He; Mingyuan Zhang; Qiang Ning; Dan Roth; | emnlp | 2021-11-05 |
| 503 | Toward Deconfounding The Effect of Entity Demographics for Question Answering Accuracy Literature Review Related Patents Related Grants Related Orgs Related Experts Details Abstract: The goal of question answering (QA) is to answer _any_ question. However, major QA datasets have skewed distributions over gender, profession, and nationality. Despite that skew, … |
Maharshi Gor; Kellie Webster; Jordan Boyd-Graber; | emnlp | 2021-11-05 |
| 504 | FewshotQA: A Simple Framework for Few-shot Learning of Question Answering Tasks Using Pre-trained Text-to-text Models Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this, we propose a simple fine-tuning framework that leverages pre-trained text-to-text models and is directly aligned with their pre-training framework. |
Rakesh Chada; Pradeep Natarajan; | emnlp | 2021-11-05 |
| 505 | Neural Natural Logic Inference for Interpretable Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate a neural-symbolic QA approach that integrates natural logic reasoning within deep learning architectures, towards developing effective and yet explainable question answering models. |
Jihao Shi; Xiao Ding; Li Du; Ting Liu; Bing Qin; | emnlp | 2021-11-05 |
| 506 | CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a semi-automatic framework for generating disentangled shifts by introducing a controllable visual question-answer generation (VQAG) module that is capable of generating highly-relevant and diverse question-answer pairs with the desired dataset style. |
ARJUN AKULA et. al. | emnlp | 2021-11-05 |
| 507 | Contrastive Domain Adaptation for Question Answering Using Limited Text Corpora Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel framework for domain adaptation called contrastive domain adaptation for QA (CAQA). |
Zhenrui Yue; Bernhard Kratzwald; Stefan Feuerriegel; | emnlp | 2021-11-05 |
| 508 | Narrative Embedding: Re-Contextualization Through Attention Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel approach for narrative event representation using attention to re-contextualize events across the whole story. |
Sean Wilner; Daniel Woolridge; Madeleine Glick; | emnlp | 2021-11-05 |
| 509 | Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a model that explicitly handles multiple-entity questions by implementing a new intersection operation, which identifies the shared elements between two sets of entities. |
Priyanka Sen; Armin Oliya; Amir Saffari; | emnlp | 2021-11-05 |
| 510 | Single-dataset Experts for Multi-dataset Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our approach is to model multi-dataset question answering with an ensemble of single-dataset experts, by training a collection of lightweight, dataset-specific adapter modules (Houlsby et al., 2019) that share an underlying Transformer model. |
Dan Friedman; Ben Dodge; Danqi Chen; | emnlp | 2021-11-05 |
| 511 | Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce various ways to retrieve knowledge using text and images and two reader styles: classification and extraction. |
Man Luo; Yankai Zeng; Pratyay Banerjee; Chitta Baral; | emnlp | 2021-11-05 |
| 512 | Joint Passage Ranking for Diverse Multi-Answer Retrieval Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce JPR, a joint passage retrieval model focusing on reranking. |
Sewon Min; Kenton Lee; Ming-Wei Chang; Kristina Toutanova; Hannaneh Hajishirzi; | emnlp | 2021-11-05 |
| 513 | Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalization Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a new parameterization of set-valued retrieval that handles unanswerable queries, and we show that marginalizing over this set during training allows a model to mitigate false negatives in supporting evidence annotations. |
Ansong Ni; Matt Gardner; Pradeep Dasigi; | emnlp | 2021-11-05 |
| 514 | FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop FiD-Ex, which addresses these shortcomings for seq2seq models by: 1) introducing sentence markers to eliminate explanation fabrication by encouraging extractive generation, 2) using the fusion-in-decoder architecture to handle long input contexts, and 3) intermediate fine-tuning on re-structured open domain QA datasets to improve few-shot performance. |
KUSHAL LAKHOTIA et. al. | emnlp | 2021-11-05 |
| 515 | Discovering The Unknown Knowns: Turning Implicit Knowledge in The Dataset Into Explicit Training Examples for Visual Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Building upon these insights, we present a simple data augmentation pipeline SimpleAug to turn this known knowledge into training examples for VQA. |
Jihyung Kil; Cheng Zhang; Dong Xuan; Wei-Lun Chao; | emnlp | 2021-11-05 |
| 516 | Reducing The Impact of Out of Vocabulary Words in The Translation of Natural Language Questions Into SPARQL Queries Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we combine Named Entity Linking, Named Entity Recognition, and Neural Machine Translation to perform automatic translation of natural language questions into SPARQL queries. |
Manuel A. Borroto Santana; Francesco Ricca; Bernardo Cuteri; | arxiv-cs.CL | 2021-11-04 |
| 517 | Medicines Question Answering System, MeQA Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present the first system in Spanish capable of answering questions about medicines for human use, called MeQA (Medicines Question Answering), a project created by the Spanish Agency for Medicines and Health Products (AEMPS, for its acronym in Spanish). |
Jesús Santamaría; | arxiv-cs.CL | 2021-11-04 |
| 518 | SERC: Syntactic and Semantic Sequence Based Event Relation Classification Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: So we propose a joint model that incorporates both temporal and causal features to perform causal relation classification. |
Kritika Venkatachalam; Raghava Mutharaju; Sumit Bhatia; | arxiv-cs.CL | 2021-11-03 |
| 519 | UQuAD1.0: Development of An Urdu Question Answering Training Data for Machine Reading Comprehension Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we used two types of MRC models: rule-based baseline and advanced Transformer-based models. |
Samreen Kazi; Shakeel Khoja; | arxiv-cs.CL | 2021-11-02 |
| 520 | Enhanced Language Representation with Label Knowledge for Span Extraction Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Recent works introduce the label knowledge to enhance the text representation by formalizing the span extraction task into a question answering problem (QA Formalization), which achieves state-of-the-art performance. |
Pan Yang; Xin Cong; Zhenyun Sun; Xingwu Liu; | arxiv-cs.CL | 2021-11-01 |
| 521 | Discourse Comprehension: A Question Answering Framework to Represent Sentence Connections Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a novel paradigm that enables scalable data collection targeting the comprehension of news documents, viewing these questions through the lens of discourse. |
WEI-JEN KO et. al. | arxiv-cs.CL | 2021-11-01 |
| 522 | DSC-IITISM at FinCausal 2021: Combining POS Tagging with Attention-based Contextual Representations for Identifying Causal Relationships in Financial Documents Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we explore several methods to identify and extract cause-effect pairs in financial documents using transformers. |
Gunjan Haldar; Aman Mittal; Pradyumna Gupta; | arxiv-cs.CL | 2021-10-31 |
| 523 | Text Classification for Task-based Source Code Related Questions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we develop a two-fold deep learning model: Seq2Seq and a binary classifier that takes in the intent (which is in natural language) and code snippets in Python. |
Sairamvinay Vijayaraghavan; Jinxiao Song; David Tomassi; Siddhartha Punj; Jailan Sabet; | arxiv-cs.SE | 2021-10-31 |
| 524 | Path-Enhanced Multi-Relational Question Answering with Knowledge Graph Embeddings Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a Path and Knowledge Embedding-Enhanced multi-relational Question Answering model (PKEEQA), which leverages multi-hop paths between entities in the KG to evaluate the ambipolar correlation between a path embedding and a multi-relational question embedding via a customizable path representation mechanism, benefiting for achieving more accurate answers from the perspective of both the triple facts and the extra paths. |
GUANGLIN NIU et. al. | arxiv-cs.CL | 2021-10-29 |
| 525 | Learning Representations for Zero-Shot Retrieval Over Structured Data Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our proposed method, analogues to a passage retrieval model in traditional Question-Answering systems, describes an architecture to discern the correct table pertaining to a given query from amongst a large pool of candidate tables. |
Harsh Kohli; | arxiv-cs.IR | 2021-10-29 |
| 526 | Multi-stage Clarification in Conversational AI: The Case of Question-Answering Dialogue Systems Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, we propose a multi-stage clarification mechanism for prompting clarification and query selection in the context of a question answering dialogue system. |
Hadrien Lautraite; Nada Naji; Louis Marceau; Marc Queudot; Eric Charton; | arxiv-cs.CL | 2021-10-28 |
| 527 | Dense Hierarchical Retrieval for Open-Domain Question Answering Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose Dense Hierarchical Retrieval (DHR), a hierarchical framework that can generate accurate dense representations of passages by utilizing both macroscopic semantics in the document and microscopic semantics specific to each passage. |
YE LIU et. al. | arxiv-cs.IR | 2021-10-28 |
| 528 | What Makes Us Curious? Analysis of A Corpus of Open-domain Questions Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper describes what information we extracted from the automated analysis of the WTC corpus of open-domain questions. |
Zhaozhen Xu; Amelia Howarth; Nicole Briggs; Nello Cristianini; | arxiv-cs.CL | 2021-10-28 |
| 529 | Vector-valued Distance and Gyrocalculus on The Space of Symmetric Positive Definite Matrices Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose the use of the vector-valued distance to compute distances and extract geometric information from the manifold of symmetric positive definite matrices (SPD), and develop gyrovector calculus, constructing analogs of vector space operations in this curved space. |
Federico López; Beatrice Pozzetti; Steve Trettel; Michael Strube; Anna Wienhard; | arxiv-cs.LG | 2021-10-26 |
| 530 | Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable Literature Review Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Relation Extractor-Reader and Comparator (RERC), a three-stage framework based on complex question decomposition, which is the first work that the RERC model has been proposed and applied in solving the multi-hop QA challenges. |
Ruiliu Fu; Han Wang; Xuejun Zhang; Jun Zhou; |