Paper Digest: Recent Papers on Machine Translation
Paper Digest Team extracted all recent Machine Translation related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.
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TABLE 1: Paper Digest: Recent Papers on Machine Translation
| Paper | Author(s) | Source | Date | |
|---|---|---|---|---|
| 1 | Translating Step-by-Step: Decomposing The Translation Process for Improved Translation Quality of Long-Form Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we present a step-by-step approach to long-form text translation, drawing on established processes in translation studies. |
Eleftheria Briakou; Jiaming Luo; Colin Cherry; Markus Freitag; | arxiv-cs.CL | 2024-09-10 |
| 2 | Evaluation of Google Translate for Mandarin Chinese Translation Using Sentiment and Semantic Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we provide an automated assessment of machine translation models with human experts using sentiment and semantic analysis. |
Xuechun Wang; Rodney Beard; Rohitash Chandra; | arxiv-cs.CL | 2024-09-08 |
| 3 | Open Language Data Initiative: Advancing Low-Resource Machine Translation for Karakalpak Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study presents several contributions for the Karakalpak language: a FLORES+ devtest dataset translated to Karakalpak, parallel corpora for Uzbek-Karakalpak, Russian-Karakalpak and English-Karakalpak of 100,000 pairs each and open-sourced fine-tuned neural models for translation across these languages. |
Mukhammadsaid Mamasaidov; Abror Shopulatov; | arxiv-cs.CL | 2024-09-06 |
| 4 | Creating Domain-Specific Translation Memories for Machine Translation Fine-tuning: The TRENCARD Bilingual Cardiology Corpus Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The article introduces a semi-automatic TM preparation methodology leveraging primarily translation tools used by translators in favor of data quality and control by the translators. |
Gokhan Dogru; | arxiv-cs.CL | 2024-09-04 |
| 5 | A Data Selection Approach for Enhancing Low Resource Machine Translation Using Cross-Lingual Sentence Representations Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To mitigate the impact of data quality issues, we propose a data filtering approach based on cross-lingual sentence representations. |
Nidhi Kowtal; Tejas Deshpande; Raviraj Joshi; | arxiv-cs.CL | 2024-09-04 |
| 6 | Towards Cross-Lingual Explanation of Artwork in Large-scale Vision Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In addition, multilingual QA benchmarks that create datasets using machine translation have cultural differences and biases, remaining issues for use as evaluation tasks. To address these challenges, this study created an extended dataset in multiple languages without relying on machine translation. |
SHINTARO OZAKI et. al. | arxiv-cs.CL | 2024-09-02 |
| 7 | Towards Tailored Recovery of Lexical Diversity in Literary Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel approach that consists of reranking translation candidates with a classifier that distinguishes between original and translated text. |
Esther Ploeger; Huiyuan Lai; Rik van Noord; Antonio Toral; | arxiv-cs.CL | 2024-08-30 |
| 8 | MQM-Chat: Multidimensional Quality Metrics for Chat Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recognizing the need for a precise evaluation metric to address the issues of chat translation, this study introduces Multidimensional Quality Metrics for Chat Translation (MQM-Chat). |
Yunmeng Li; Jun Suzuki; Makoto Morishita; Kaori Abe; Kentaro Inui; | arxiv-cs.CL | 2024-08-29 |
| 9 | Instruction-tuned Large Language Models for Machine Translation in The Medical Domain Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we compare the performance between baseline LLMs and instruction-tuned LLMs in the medical domain. |
Miguel Rios; | arxiv-cs.CL | 2024-08-29 |
| 10 | From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation Systems: Survey, Taxonomy and Performance Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, there are few works on sign language machine translation considering the particularity of the language being continuous and dynamic. This paper aims to address this void, providing a retrospective analysis of the temporal evolution of sign language machine translation algorithms and a taxonomy of the Transformers architectures, the most used approach in language translation. |
Nada Shahin; Leila Ismail; | arxiv-cs.AI | 2024-08-27 |
| 11 | FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to help converge the fields, we introduce FLEURS-ASL, an extension of the multiway parallel benchmarks FLORES (for text) and FLEURS (for speech) to support their first sign language (as video), American Sign Language, translated by 5 Certified Deaf Interpreters. |
Garrett Tanzer; | arxiv-cs.CL | 2024-08-24 |
| 12 | Cultural Adaptation of Menus: A Fine-Grained Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce the ChineseMenuCSI dataset, the largest for Chinese-English menu corpora, annotated with CSI vs Non-CSI labels and a fine-grained test set. |
Zhonghe Zhang; Xiaoyu He; Vivek Iyer; Alexandra Birch; | arxiv-cs.CL | 2024-08-24 |
| 13 | Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate three pivotal aspects: enhancing the domain-specific quality of NMT by fine-tuning domain-relevant data from different language pairs, identifying which domains are transferable in zero-shot scenarios, and assessing the impact of language-specific versus domain-specific factors on adaptation effectiveness. |
Lia Shahnazaryan; Meriem Beloucif; | arxiv-cs.CL | 2024-08-21 |
| 14 | Expanding FLORES+ Benchmark for More Low-Resource Settings: Portuguese-Emakhuwa Machine Translation Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present baseline results from training a Neural Machine Translation system and fine-tuning existing multilingual translation models. |
Felermino D. M. Antonio Ali; Henrique Lopes Cardoso; Rui Sousa-Silva; | arxiv-cs.CL | 2024-08-21 |
| 15 | Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we address key challenges facing LLMs fine-tuned for SimulMT, validate classical SimulMT concepts and practices in the context of LLMs, explore adapting LLMs that are fine-tuned for NMT to the task of SimulMT, and introduce Simul-LLM, the first open-source fine-tuning and evaluation pipeline development framework for LLMs focused on SimulMT. |
Victor Agostinelli; Max Wild; Matthew Raffel; Kazi Fuad; Lizhong Chen; | acl | 2024-08-20 |
| 16 | TasTe: Teaching Large Language Models to Translate Through Self-Reflection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose the TasTe framework, which stands for translating through self-reflection. |
YUTONG WANG et. al. | acl | 2024-08-20 |
| 17 | Document-Level Machine Translation with Large-Scale Public Parallel Corpora Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We release a large-scale open parallel corpus with document context extracted from ParaCrawl in five language pairs, along with code to compile document-level datasets for any language pair supported by ParaCrawl. We train context-aware models on these datasets and find improvements in terms of overall translation quality and targeted document-level phenomena. |
Proyag Pal; Alexandra Birch; Kenneth Heafield; | acl | 2024-08-20 |
| 18 | Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language Representations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce Babel-ImageNet, a massively multilingual benchmark that offers (partial) translations of ImageNet labels to 100 languages, built without machine translation or manual annotation. |
Gregor Geigle; Radu Timofte; Goran Glava�; | acl | 2024-08-20 |
| 19 | Large Language Models Are No Longer Shallow Parsers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on analyzing and improving the capability of current state-of-the-art LLMs on a classic fundamental task, namely constituency parsing, which is the representative syntactic task in both linguistics and natural language processing. |
Yuanhe Tian; Fei Xia; Yan Song; | acl | 2024-08-20 |
| 20 | The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our findings emphasize the need for fine-tuning strategies that preserve the benefits of LLMs for machine translation. |
David Stap; Eva Hasler; Bill Byrne; Christof Monz; Ke Tran; | acl | 2024-08-20 |
| 21 | Self-Modifying State Modeling for Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Besides, building decision paths requires unidirectional encoders to simulate streaming source inputs, which impairs the translation quality of SiMT models. To solve these issues, we propose Self-Modifying State Modeling (SM2), a novel training paradigm for SiMT task. |
Donglei Yu; Xiaomian Kang; Yuchen Liu; Yu Zhou; Chengqing Zong; | acl | 2024-08-20 |
| 22 | Speech Sense Disambiguation: Tackling Homophone Ambiguity in End-to-End Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To facilitate this, we first create a comprehensive homophone dictionary and an annotated dataset rich with homophone information established based on speech-text alignment. Building on this unique dictionary, we introduce AmbigST, an innovative homophone-aware contrastive learning approach that integrates a homophone-aware masking strategy. |
TENGFEI YU et. al. | acl | 2024-08-20 |
| 23 | What Is The Best Way for ChatGPT to Translate Poetry? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite promising outcomes, our analysis reveals persistent issues in the translations generated by ChatGPT that warrant attention. To address these shortcomings, we propose an Explanation-Assisted Poetry Machine Translation (EAPMT) method, which leverages monolingual poetry explanation as a guiding information for the translation process. |
Shanshan Wang; Derek Wong; Jingming Yao; Lidia Chao; | acl | 2024-08-20 |
| 24 | GenTranslate: Large Language Models Are Generative Multilingual Speech and Machine Translators Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new generative paradigm for translation tasks, namely GenTranslate, which builds upon LLMs to generate better results from the diverse translation versions in N-best list. |
YUCHEN HU et. al. | acl | 2024-08-20 |
| 25 | Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Intuitively, with a growing number of seen languages the encoder sentence representation grows more flexible and easily adaptable to new languages. In this work, we test this hypothesis by zero-shot translating from unseen languages. |
Carlos Mullov; Quan Pham; Alexander Waibel; | acl | 2024-08-20 |
| 26 | Cross-Lingual Conversational Speech Summarization with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We build a baseline cascade-based system using open-source speech recognition and machine translation models. |
Max Nelson; Shannon Wotherspoon; Francis Keith; William Hartmann; Matthew Snover; | arxiv-cs.CL | 2024-08-12 |
| 27 | Simplifying Translations for Children: Iterative Simplification Considering Age of Acquisition with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we propose a method that replaces words with high Age of Acquisitions (AoA) in translations with simpler words to match the translations to the user’s level. |
Masashi Oshika; Makoto Morishita; Tsutomu Hirao; Ryohei Sasano; Koichi Takeda; | arxiv-cs.CL | 2024-08-08 |
| 28 | Evaluating The Translation Performance of Large Language Models Based on Euas-20 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite the significant progress in translation performance achieved by large language models, machine translation still faces many challenges. Therefore, in this paper, we construct the dataset Euas-20 to evaluate the performance of large language models on translation tasks, the translation ability on different languages, and the effect of pre-training data on the translation ability of LLMs for researchers and developers. |
Yan Huang; Wei Liu; | arxiv-cs.CL | 2024-08-06 |
| 29 | Conditioning LLMs with Emotion in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel MT pipeline that integrates emotion information extracted from a Speech Emotion Recognition (SER) model into LLMs to enhance translation quality. |
Charles Brazier; Jean-Luc Rouas; | arxiv-cs.CL | 2024-08-06 |
| 30 | BOTS-LM: Training Large Language Models for Setswana Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we present BOTS-LM, a series of bilingual language models proficient in both Setswana and English. |
Nathan Brown; Vukosi Marivate; | arxiv-cs.CL | 2024-08-05 |
| 31 | Decoupled Vocabulary Learning Enables Zero-Shot Translation from Unseen Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Intuitively, with a growing number of seen languages the encoder sentence representation grows more flexible and easily adaptable to new languages. In this work, we test this hypothesis by zero-shot translating from unseen languages. |
Carlos Mullov; Ngoc-Quan Pham; Alexander Waibel; | arxiv-cs.CL | 2024-08-05 |
| 32 | Improving Multilingual Neural Machine Translation By Utilizing Semantic and Linguistic Features Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we propose to exploit both semantic and linguistic features between multiple languages to enhance multilingual translation. |
Mengyu Bu; Shuhao Gu; Yang Feng; | arxiv-cs.CL | 2024-08-02 |
| 33 | In-Context Example Selection Via Similarity Search Improves Low-Resource Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on machine translation (MT), a task that has been shown to benefit from in-context translation examples. |
Armel Zebaze; Benoît Sagot; Rachel Bawden; | arxiv-cs.CL | 2024-08-01 |
| 34 | Generating Gender Alternatives in Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our key technical contribution is a novel semi-supervised solution for generating alternatives that integrates seamlessly with standard MT models and maintains high performance without requiring additional components or increasing inference overhead. |
SARTHAK GARG et. al. | arxiv-cs.CL | 2024-07-29 |
| 35 | The Power of Prompts: Evaluating and Mitigating Gender Bias in MT with LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our findings reveal pervasive gender bias across all models, with base LLMs exhibiting a higher degree of bias compared to NMT models. To combat this bias, we explore prompting engineering techniques applied to an instruction-tuned LLM. |
Aleix Sant; Carlos Escolano; Audrey Mash; Francesca De Luca Fornaciari; Maite Melero; | arxiv-cs.CL | 2024-07-26 |
| 36 | Beyond Binary Gender: Evaluating Gender-Inclusive Machine Translation with Ambiguous Attitude Words Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Gender bias has been a focal point in the study of bias in machine translation and language models. |
YIJIE CHEN et. al. | arxiv-cs.CL | 2024-07-23 |
| 37 | Machine Translation Hallucination Detection for Low and High Resource Languages Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper evaluates hallucination detection approaches using Large Language Models (LLMs) and semantic similarity within massively multilingual embeddings. |
KENZA BENKIRANE et. al. | arxiv-cs.CL | 2024-07-23 |
| 38 | Fine-grained Gender Control in Machine Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle controlled translation in a more realistic setting of inputs with multiple entities and propose Gender-of-Entity (GoE) prompting method for LLMs. |
Minwoo Lee; Hyukhun Koh; Minsung Kim; Kyomin Jung; | arxiv-cs.CL | 2024-07-21 |
| 39 | CoVoSwitch: Machine Translation of Synthetic Code-Switched Text Based on Intonation Units Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: With our dataset, CoVoSwitch, spanning 13 languages, we evaluate the code-switching translation performance of two multilingual translation models, M2M-100 418M and NLLB-200 600M. |
Yeeun Kang; | arxiv-cs.CL | 2024-07-19 |
| 40 | Translate-and-Revise: Boosting Large Language Models for Constrained Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Imposing constraints on machine translation systems presents a challenging issue because these systems are not trained to make use of constraints in generating adequate, fluent translations. In this paper, we leverage the capabilities of large language models (LLMs) for constrained translation, given that LLMs can easily adapt to this task by taking translation instructions and constraints as prompts. |
PENGCHENG HUANG et. al. | arxiv-cs.CL | 2024-07-18 |
| 41 | Towards Zero-Shot Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a method to bypass the need for fully supervised data to train MMT systems, using multimodal English data only. |
Matthieu Futeral; Cordelia Schmid; Benoît Sagot; Rachel Bawden; | arxiv-cs.CL | 2024-07-18 |
| 42 | LLMs-in-the-loop Part-1: Expert Small AI Models for Bio-Medical Text Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study introduces a novel LLMs-in-the-loop approach to develop supervised neural machine translation models optimized specifically for medical texts. |
Bunyamin Keles; Murat Gunay; Serdar I. Caglar; | arxiv-cs.CL | 2024-07-16 |
| 43 | Scaling Sign Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we push forward the frontier of SLT by scaling pretraining data, model size, and number of translation directions. |
Biao Zhang; Garrett Tanzer; Orhan Firat; | arxiv-cs.CL | 2024-07-16 |
| 44 | Towards Chapter-to-Chapter Context-Aware Literary Translation Via Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Through our comprehensive analysis, we unveil that literary translation under the Ch2Ch setting is challenging in nature, with respect to both model learning methods and translation decoding algorithms. |
Linghao Jin; Li An; Xuezhe Ma; | arxiv-cs.CL | 2024-07-12 |
| 45 | Rule-Based, Neural and LLM Back-Translation: Comparative Insights from A Variant of Ladin Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the impact of different back-translation approaches on machine translation for Ladin, specifically the Val Badia variant. |
Samuel Frontull; Georg Moser; | arxiv-cs.CL | 2024-07-11 |
| 46 | Segment-Based Interactive Machine Translation for Pre-trained Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Pre-trained large language models (LLM) are starting to be widely used in many applications. In this work, we explore the use of these models in interactive machine translation (IMT) environments. |
Angel Navarro; Francisco Casacuberta; | arxiv-cs.CL | 2024-07-09 |
| 47 | A Word Order Synchronization Metric for Evaluating Simultaneous Interpretation and Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose an automatic evaluation metric for SI and SiMT focusing on word order synchronization. |
Mana Makinae; Katsuhito Sudoh; Mararu Yamada; Satoshi Nakamura; | arxiv-cs.CL | 2024-07-09 |
| 48 | Identifying Intensity of The Structure and Content in Tweets and The Discriminative Power of Attributes in Context with Referential Translation Machines Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We use referential translation machines (RTMs) to identify the similarity between an attribute and two words in English by casting the task as machine translation performance prediction (MTPP) between the words and the attribute word and the distance between their similarities for Task 10 with stacked RTM models. |
Ergun Biçici; | arxiv-cs.CL | 2024-07-06 |
| 49 | Enhancing Language Learning Through Technology: Introducing A New English-Azerbaijani (Arabic Script) Parallel Corpus Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces a pioneering English-Azerbaijani (Arabic Script) parallel corpus, designed to bridge the technological gap in language learning and machine translation (MT) for under-resourced languages. |
JALIL NOURMOHAMMADI KHIARAK et. al. | arxiv-cs.CL | 2024-07-06 |
| 50 | Toucan: Many-to-Many Translation for 150 African Language Pairs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work aims to advance the field of NLP, fostering cross-cultural understanding and knowledge exchange, particularly in regions with limited language resources such as Africa. |
AbdelRahim Elmadany; Ife Adebara; Muhammad Abdul-Mageed; | arxiv-cs.CL | 2024-07-05 |
| 51 | Finetuning End-to-End Models for Estonian Conversational Spoken Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluated three publicly available end-to-end models: Whisper, OWSM 3.1, and SeamlessM4T. |
Tiia Sildam; Andra Velve; Tanel Alumäe; | arxiv-cs.CL | 2024-07-04 |
| 52 | A Case Study on Context-Aware Neural Machine Translation with Multi-Task Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We conduct experiments on cascade MTL architecture, which consists of one encoder and two decoders. |
Ramakrishna Appicharla; Baban Gain; Santanu Pal; Asif Ekbal; Pushpak Bhattacharyya; | arxiv-cs.CL | 2024-07-03 |
| 53 | Evaluating Automatic Metrics with Incremental Machine Translation Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a dataset comprising commercial machine translations, gathered weekly over six years across 12 translation directions. |
Guojun Wu; Shay B. Cohen; Rico Sennrich; | arxiv-cs.CL | 2024-07-03 |
| 54 | Language Portability Strategies for Open-domain Dialogue with Pre-trained Language Models from High to Low Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we propose a study of linguistic portability strategies of large pre-trained language models (PLMs) used for open-domain dialogue systems in a high-resource language for this task. |
Ahmed Njifenjou; Virgile Sucal; Bassam Jabaian; Fabrice Lefèvre; | arxiv-cs.CL | 2024-07-01 |
| 55 | Towards Massive Multilingual Holistic Bias Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the current landscape of automatic language generation, there is a need to understand, evaluate, and mitigate demographic biases as existing models are becoming increasingly multilingual. To address this, we present the initial eight languages from the MASSIVE MULTILINGUAL HOLISTICBIAS (MMHB) dataset and benchmark consisting of approximately 6 million sentences representing 13 demographic axes. |
XIAOQING ELLEN TAN et. al. | arxiv-cs.CL | 2024-06-29 |
| 56 | Less Is More: Accurate Speech Recognition & Translation Without Web-Scale Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We argue that state-of-the art accuracy can be reached without relying on web-scale data. |
KRISHNA C. PUVVADA et. al. | arxiv-cs.CL | 2024-06-28 |
| 57 | Sparse Regression for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce \textit{dice} instance selection method for proper selection of training instances, which plays an important role to learn correct feature mappings for improving the source and target coverage of the training set. |
Ergun Biçici; | arxiv-cs.CL | 2024-06-27 |
| 58 | XTower: A Multilingual LLM for Explaining and Correcting Translation Errors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces xTower, an open large language model (LLM) built on top of TowerBase designed to provide free-text explanations for translation errors in order to guide the generation of a corrected translation. |
MARCOS TREVISO et. al. | arxiv-cs.CL | 2024-06-27 |
| 59 | FFN: A Fine-grained Chinese-English Financial Domain Parallel Corpus Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For comparison, we also trained an OpenNMT model based on our dataset. We detail problems of LLMs and provide in-depth analysis, intending to stimulate further research and solutions in this largely uncharted territory. |
Yuxin Fu; Shijing Si; Leyi Mai; Xi-ang Li; | arxiv-cs.CL | 2024-06-26 |
| 60 | ArzEn-LLM: Code-Switched Egyptian Arabic-English Translation and Speech Recognition Using LLMs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Motivated by the widespread increase in the phenomenon of code-switching between Egyptian Arabic and English in recent times, this paper explores the intricacies of machine translation (MT) and automatic speech recognition (ASR) systems, focusing on translating code-switched Egyptian Arabic-English to either English or Egyptian Arabic. Our goal is to present the methodologies employed in developing these systems, utilizing large language models such as LLama and Gemma. |
Ahmed Heakl; Youssef Zaghloul; Mennatullah Ali; Rania Hossam; Walid Gomaa; | arxiv-cs.CL | 2024-06-26 |
| 61 | Document Image Machine Translation with Dynamic Multi-pre-trained Models Assembling Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we extend the current TIMT task and propose a novel task, **D**ocument **I**mage **M**achine **T**ranslation to **Markdown** (**DIMT2Markdown**), which aims to translate a source document image with long context and complex layout structure to markdown-formatted target translation. |
YUPU LIANG et. al. | naacl | 2024-06-20 |
| 62 | Do Multilingual Language Models Think Better in English? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce a new approach called self-translate that leverages the few-shot translation capabilities of multilingual language models. |
Julen Etxaniz; Gorka Azkune; Aitor Soroa; Oier Lacalle; Mikel Artetxe; | naacl | 2024-06-20 |
| 63 | Contextual Label Projection for Cross-Lingual Structured Prediction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce a novel label projection approach, CLaP, which translates text to the target language and performs *contextual translation* on the labels using the translated text as the context, ensuring better accuracy for the translated labels. |
Tanmay Parekh; I-Hung Hsu; Kuan-Hao Huang; Kai-Wei Chang; Nanyun Peng; | naacl | 2024-06-20 |
| 64 | M3T: A New Benchmark Dataset for Multi-Modal Document-Level Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This complexity is particularly evident in widely used PDF documents, which represent information visually. This paper addresses this gap by introducing M3T a novel benchmark dataset tailored to evaluate NMT systems on the comprehensive task of translating semi-structured documents. |
BENJAMIN HSU et. al. | naacl | 2024-06-20 |
| 65 | Contextual Refinement of Translations: Large Language Models for Sentence and Document-Level Post-Editing Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Surprisingly, our initial experiments found that fine-tuning with Q-LoRA for translation purposes led to performance improvements in terms of BLEU but degradation in COMET compared to in-context learning. To overcome this, we propose an alternative approach: adapting LLMs as Automatic Post-Editors (APE) rather than direct translators. |
Sai Koneru; Miriam Exel; Matthias Huck; Jan Niehues; | naacl | 2024-06-20 |
| 66 | IndiSentiment140: Sentiment Analysis Dataset for Indian Languages with Emphasis on Low-Resource Languages Using Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The study aims to provide insights into the practicality of using machine translation in the context of India�s linguistic diversity for sentiment analysis datasets. |
Saurabh Kumar; Ranbir Sanasam; Sukumar Nandi; | naacl | 2024-06-20 |
| 67 | An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we conduct empirical studies on intra-modal and cross-modal consistency and propose two training strategies, SimRegCR and SimZeroCR, for E2E ST in regular and zero-shot scenarios. |
Pengzhi Gao; Ruiqing Zhang; Zhongjun He; Hua Wu; Haifeng Wang; | naacl | 2024-06-20 |
| 68 | MT-PATCHER: Selective and Extendable Knowledge Distillation from Large Language Models for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a framework called MT-Patcher, which transfers knowledge from LLMs to existing MT models in a selective, comprehensive and proactive manner. |
Jiahuan Li; Shanbo Cheng; Shujian Huang; Jiajun Chen; | naacl | 2024-06-20 |
| 69 | Fixing Rogue Memorization in Many-to-One Multilingual Translators of Extremely-Low-Resource Languages By Rephrasing Training Samples Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we study the fine-tuning of pre-trained large high-resource language models (LLMs) into many-to-one multilingual machine translators for extremely-low-resource languages such as endangered Indigenous languages. |
Paulo Cavalin; Pedro Henrique Domingues; Claudio Pinhanez; Julio Nogima; | naacl | 2024-06-20 |
| 70 | Complexity of Symbolic Representation in Working Memory of Transformer Correlates with The Complexity of A Task Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores the properties of the content of symbolic working memory added to the Transformer model decoder. |
Alsu Sagirova; Mikhail Burtsev; | arxiv-cs.CL | 2024-06-20 |
| 71 | Grammar-based Data Augmentation for Low-Resource Languages: The Case of Guarani-Spanish Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One of the main problems low-resource languages face in NLP can be pictured as a vicious circle: data is needed to build and test tools, but the available text is scarce and there are not powerful tools to collect it. In order to break this circle for Guarani, we explore if text automatically generated from a grammar can work as a Data Augmentation technique to boost the performance of Guarani-Spanish Machine Translation (MT) systems. |
AGUST�N LUCAS et. al. | naacl | 2024-06-20 |
| 72 | Translating Across Cultures: LLMs for Intralingual Cultural Adaptation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: LLMs on the other hand have a rich reservoir of cultural knowledge embedded within its parameters that can be potentially exploited for such applications. In this paper we define the task of cultural adaptation and create an evaluation framework to benchmark different models for this task. |
Pushpdeep Singh; Mayur Patidar; Lovekesh Vig; | arxiv-cs.CL | 2024-06-20 |
| 73 | How Effective Is Multi-source Pivoting for Translation of Low Resource Indian Languages? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Taking the case of English to Indian language MT, this paper explores the ‘multi-source translation’ approach with pivoting, using both source and pivot sentences to improve translation. |
Pranav Gaikwad; Meet Doshi; Raj Dabre; Pushpak Bhattacharyya; | arxiv-cs.CL | 2024-06-19 |
| 74 | Evaluating Structural Generalization in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address this question, we construct SGET, a machine translation dataset covering various types of compositional generalization with control of words and sentence structures. We evaluate neural machine translation models on SGET and show that they struggle more in structural generalization than in lexical generalization. |
Ryoma Kumon; Daiki Matsuoka; Hitomi Yanaka; | arxiv-cs.CL | 2024-06-19 |
| 75 | Low-Resource Machine Translation Through The Lens of Personalized Federated Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a new approach based on the Personalized Federated Learning algorithm MeritFed that can be applied to Natural Language Tasks with heterogeneous data. |
VIKTOR MOSKVORETSKII et. al. | arxiv-cs.CL | 2024-06-18 |
| 76 | Does Context Help Mitigate Gender Bias in Neural Machine Translation? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Context-aware models have been previously suggested as a means to mitigate this type of bias. In this work, we examine this claim by analysing in detail the translation of stereotypical professions in English to German, and translation with non-informative context in Basque to Spanish. |
Harritxu Gete; Thierry Etchegoyhen; | arxiv-cs.CL | 2024-06-18 |
| 77 | Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we get the best both worlds by integrating MT encoders directly into LLM backbones via sample-efficient self-distillation. |
Fabian David Schmidt; Philipp Borchert; Ivan Vulić; Goran Glavaš; | arxiv-cs.CL | 2024-06-18 |
| 78 | Error Span Annotation: A Balanced Approach for Human Evaluation of Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce Error Span Annotation (ESA), a human evaluation protocol which combines the continuous rating of DA with the high-level error severity span marking of MQM. |
TOM KOCMI et. al. | arxiv-cs.CL | 2024-06-17 |
| 79 | LiLiuM: EBay’s Large Language Models for E-commerce Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce the LiLiuM series of large language models (LLMs): 1B, 7B, and 13B parameter models developed 100% in-house to fit eBay’s specific needs in the e-commerce domain. |
CHRISTIAN HEROLD et. al. | arxiv-cs.CL | 2024-06-17 |
| 80 | Reconsidering Sentence-Level Sign Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Historically, sign language machine translation has been posed as a sentence-level task: datasets consisting of continuous narratives are chopped up and presented to the model as isolated clips. In this work, we explore the limitations of this task framing. |
Garrett Tanzer; Maximus Shengelia; Ken Harrenstien; David Uthus; | arxiv-cs.CL | 2024-06-16 |
| 81 | CoSTA: Code-Switched Speech Translation Using Aligned Speech-Text Interleaving Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on the problem of spoken translation (ST) of code-switched speech in Indian languages to English text. |
Bhavani Shankar; Preethi Jyothi; Pushpak Bhattacharyya; | arxiv-cs.CL | 2024-06-16 |
| 82 | Datasets for Multilingual Answer Sentence Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce new high-quality datasets for AS2 in five European languages (French, German, Italian, Portuguese, and Spanish), obtained through supervised Automatic Machine Translation (AMT) of existing English AS2 datasets such as ASNQ, WikiQA, and TREC-QA using a Large Language Model (LLM). |
Matteo Gabburo; Stefano Campese; Federico Agostini; Alessandro Moschitti; | arxiv-cs.CL | 2024-06-14 |
| 83 | Word Order in English-Japanese Simultaneous Interpretation: Analyses and Evaluation Using Chunk-wise Monotonic Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper analyzes the features of monotonic translations, which follow the word order of the source language, in simultaneous interpreting (SI). |
Kosuke Doi; Yuka Ko; Mana Makinae; Katsuhito Sudoh; Satoshi Nakamura; | arxiv-cs.CL | 2024-06-13 |
| 84 | Towards Multilingual Audio-Visual Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we work towards extending Audio-Visual Question Answering (AVQA) to multilingual settings. |
ORCHID CHETIA PHUKAN et. al. | arxiv-cs.LG | 2024-06-13 |
| 85 | M3T: A New Benchmark Dataset for Multi-Modal Document-Level Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This complexity is particularly evident in widely used PDF documents, which represent information visually. This paper addresses this gap by introducing M3T, a novel benchmark dataset tailored to evaluate NMT systems on the comprehensive task of translating semi-structured documents. |
BENJAMIN HSU et. al. | arxiv-cs.CL | 2024-06-12 |
| 86 | Guiding In-Context Learning of LLMs Through Quality Estimation for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents a novel methodology for in-context learning (ICL) that relies on a search algorithm guided by domain-specific quality estimation (QE). |
Javad Pourmostafa Roshan Sharami; Dimitar Shterionov; Pieter Spronck; | arxiv-cs.CL | 2024-06-12 |
| 87 | Agent-SiMT: Agent-assisted Simultaneous Machine Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Conversely, Large Language Models (LLMs), trained on extensive corpora, possess superior generation capabilities, but it is difficult for them to acquire translation policy through the training methods of SiMT. Therefore, we introduce Agent-SiMT, a framework combining the strengths of LLMs and traditional SiMT methods. |
Shoutao Guo; Shaolei Zhang; Zhengrui Ma; Min Zhang; Yang Feng; | arxiv-cs.CL | 2024-06-10 |
| 88 | Building Bridges: A Dataset for Evaluating Gender-Fair Machine Translation Into German Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We address this research gap by studying gender-fair language in English-to-German MT. Concretely, we enrich a community-created gender-fair language dictionary and sample multi-sentence test instances from encyclopedic text and parliamentary speeches. |
Manuel Lardelli; Giuseppe Attanasio; Anne Lauscher; | arxiv-cs.CL | 2024-06-10 |
| 89 | Recovering Document Annotations for Sentence-level Bitext Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we reconstruct document-level information for three (ParaCrawl, News Commentary, and Europarl) large datasets in German, French, Spanish, Italian, Polish, and Portuguese (paired with English). |
Rachel Wicks; Matt Post; Philipp Koehn; | arxiv-cs.CL | 2024-06-06 |
| 90 | StatBot.Swiss: Bilingual Open Data Exploration in Natural Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we release the StatBot.Swiss dataset, the first bilingual benchmark for evaluating Text-to-SQL systems based on real-world applications. |
FARHAD NOORALAHZADEH et. al. | arxiv-cs.CL | 2024-06-05 |
| 91 | What Is The Best Way for ChatGPT to Translate Poetry? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite promising outcomes, our analysis reveals persistent issues in the translations generated by ChatGPT that warrant attention. To address these shortcomings, we propose an Explanation-Assisted Poetry Machine Translation (EAPMT) method, which leverages monolingual poetry explanation as a guiding information for the translation process. |
Shanshan Wang; Derek F. Wong; Jingming Yao; Lidia S. Chao; | arxiv-cs.CL | 2024-06-05 |
| 92 | Translation Deserves Better: Analyzing Translation Artifacts in Cross-lingual Visual Question Answering Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that these artifacts can significantly affect the models, confirmed by extensive experiments across diverse models, languages, and translation processes. In light of this, we present a simple data augmentation strategy that can alleviate the adverse impacts of translation artifacts. |
CHAEHUN PARK et. al. | arxiv-cs.CL | 2024-06-04 |
| 93 | Efficient Minimum Bayes Risk Decoding Using Low-Rank Matrix Completion Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a novel approach for approximating MBR decoding using matrix completion techniques, focusing on the task of machine translation. |
Firas Trabelsi; David Vilar; Mara Finkelstein; Markus Freitag; | arxiv-cs.CL | 2024-06-04 |
| 94 | LexMatcher: Dictionary-centric Data Collection for LLM-based Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present LexMatcher, a simple yet effective method for data curation, the design of which is driven by the coverage of senses found in bilingual dictionaries. |
Yongjing Yin; Jiali Zeng; Yafu Li; Fandong Meng; Yue Zhang; | arxiv-cs.CL | 2024-06-03 |
| 95 | FaceCLIP: Facial Image-to-Video Translation Via A Brief Text Description Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The existing image-to-video translation methods generally follow a frame-by-frame generative paradigm, while extracting the temporal information from a reference video or an audio … |
JIAYI GUO et. al. | IEEE Transactions on Circuits and Systems for Video … | 2024-06-01 |
| 96 | How Multilingual Are Large Language Models Fine-Tuned for Translation? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: How does translation fine-tuning impact the MT capabilities of LLMs for zero-shot languages, zero-shot language pairs, and translation tasks that do not involve English? To address these questions, we conduct an extensive empirical evaluation of the translation quality of the TOWER family of language models (Alves et al., 2024) on 132 translation tasks from the multi-parallel FLORES-200 data. |
Aquia Richburg; Marine Carpuat; | arxiv-cs.CL | 2024-05-30 |
| 97 | Significance of Chain of Thought in Gender Bias Mitigation for English-Dravidian Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper examines gender bias in machine translation systems for languages such as Telugu and Kan- nada from the Dravidian family, analyzing how gender inflections affect translation accuracy and neutrality using Google Translate and Chat- GPT. |
Lavanya Prahallad; Radhika Mamidi; | arxiv-cs.CL | 2024-05-30 |
| 98 | Critical Learning Periods: Leveraging Early Training Dynamics for Efficient Data Pruning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a new data pruning technique: Checkpoints Across Time (CAT), that leverages early model training dynamics to identify the most relevant data points for model performance. |
EVERLYN ASIKO CHIMOTO et. al. | arxiv-cs.CL | 2024-05-29 |
| 99 | TransVIP: Speech to Speech Translation System with Voice and Isochrony Preservation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce a novel model framework TransVIP that leverages diverse datasets in a cascade fashion yet facilitates end-to-end inference through joint probability. |
CHENYANG LE et. al. | arxiv-cs.CL | 2024-05-28 |
| 100 | Optimizing Example Selection for Retrieval-augmented Machine Translation with Translation Memories Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We aim to improve the upstream retrieval step and consider a fixed downstream edit-based model: the multi-Levenshtein Transformer. |
Maxime Bouthors; Josep Crego; François Yvon; | arxiv-cs.CL | 2024-05-23 |
| 101 | Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate the role of translation and synthetic data in training language models. |
Sabri Boughorbel; MD Rizwan Parvez; Majd Hawasly; | arxiv-cs.CL | 2024-05-23 |
| 102 | A Survey on Multi-modal Machine Translation: Tasks, Methods and Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we begin by offering an exhaustive overview of 99 prior works, comprehensively summarizing representative studies from the perspectives of dominant models, datasets, and evaluation metrics. |
HUANGJUN SHEN et. al. | arxiv-cs.CL | 2024-05-21 |
| 103 | MELD-ST: An Emotion-aware Speech Translation Dataset Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present the MELD-ST dataset for the emotion-aware speech translation task, comprising English-to-Japanese and English-to-German language pairs. |
SIROU CHEN et. al. | arxiv-cs.CL | 2024-05-21 |
| 104 | DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce DiffNorm, a diffusion-based normalization strategy that simplifies data distributions for training NAT models. |
Weiting Tan; Jingyu Zhang; Lingfeng Shen; Daniel Khashabi; Philipp Koehn; | arxiv-cs.CL | 2024-05-21 |
| 105 | Beyond MLE: Investigating SEARNN for Low-Resourced Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With an average BLEU score improvement of $5.4$\% over the MLE objective, we proved that SEARNN is indeed a viable algorithm to effectively train RNNs on machine translation for low-resourced languages. |
Chris Emezue; | arxiv-cs.CL | 2024-05-20 |
| 106 | LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a new paradigm for machine translation that is particularly useful for no-resource languages (those without any publicly available bilingual or monolingual corpora): LLM-RBMT (LLM-Assisted Rule Based Machine Translation). |
Jared Coleman; Bhaskar Krishnamachari; Khalil Iskarous; Ruben Rosales; | arxiv-cs.CL | 2024-05-14 |
| 107 | Enhancing Gender-Inclusive Machine Translation with Neomorphemes and Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Accordingly, they still fall short in using gender-inclusive language, also representative of non-binary identities. In this paper, we look at gender-inclusive neomorphemes, neologistic elements that avoid binary gender markings as an approach towards fairer MT. In this direction, we explore prompting techniques with large language models (LLMs) to translate from English into Italian using neomorphemes. |
Andrea Piergentili; Beatrice Savoldi; Matteo Negri; Luisa Bentivogli; | arxiv-cs.CL | 2024-05-14 |
| 108 | CANTONMT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper investigates the development and evaluation of machine translation models from Cantonese to English, where we propose a novel approach to tackle low-resource language translations. |
Kung Yin Hong; Lifeng Han; Riza Batista-Navarro; Goran Nenadic; | arxiv-cs.CL | 2024-05-13 |
| 109 | An Empirical Study on The Robustness of Massively Multilingual Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we empirically investigate the translation robustness of Indonesian-Chinese translation in the face of various naturally occurring noise. |
Leiyu Pan; Deyi Xiong; | arxiv-cs.CL | 2024-05-13 |
| 110 | Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We analyze the challenges and propose techniques that can be tailored for Multilingual Named Entity Recognition for Indian Languages. |
SANKALP BAHAD et. al. | arxiv-cs.CL | 2024-05-08 |
| 111 | Using Machine Translation to Augment Multilingual Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Here, we explore the effects of using machine translation to fine-tune a multilingual model for a classification task across multiple languages. |
Adam King; | arxiv-cs.CL | 2024-05-08 |
| 112 | Relay Decoding: Concatenating Large Language Models for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: When it is challenging to find large models that support the desired languages, resorting to continuous learning methods becomes a costly endeavor. To mitigate these expenses, we propose an innovative approach called RD (Relay Decoding), which entails concatenating two distinct large models that individually support the source and target languages. |
CHENGPENG FU et. al. | arxiv-cs.CL | 2024-05-05 |
| 113 | Sentiment Analysis Across Languages: Evaluation Before and After Machine Translation to English Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper examines the performance of transformer models in Sentiment Analysis tasks across multilingual datasets and text that has undergone machine translation. |
Aekansh Kathunia; Mohammad Kaif; Nalin Arora; N Narotam; | arxiv-cs.CL | 2024-05-05 |
| 114 | The IgboAPI Dataset: Empowering Igbo Language Technologies Through Multi-dialectal Enrichment Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In response, we present the IgboAPI dataset, a multi-dialectal Igbo-English dictionary dataset, developed with the aim of enhancing the representation of Igbo dialects. |
CHRIS CHINENYE EMEZUE et. al. | arxiv-cs.CL | 2024-05-02 |
| 115 | Context-Aware Machine Translation with Source Coreference Explanation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This can lead to the explain-away effect, wherein the models only consider features easier to explain predictions, resulting in inaccurate translations. To address this issue, we propose a model that explains the decisions made for translation by predicting coreference features in the input. |
Huy Hien Vu; Hidetaka Kamigaito; Taro Watanabe; | arxiv-cs.CL | 2024-04-30 |
| 116 | Suvach — Generated Hindi QA Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper proposes a new benchmark specifically designed for evaluating Hindi EQA models and discusses the methodology to do the same for any task. |
Vaishak Narayanan; Prabin Raj KP; Saifudheen Nouphal; | arxiv-cs.CL | 2024-04-30 |
| 117 | Usefulness of Emotional Prosody in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose to improve translation quality by adding another external source of information: the automatically recognized emotion in the voice. |
Charles Brazier; Jean-Luc Rouas; | arxiv-cs.CL | 2024-04-27 |
| 118 | Quality Estimation with $k$-nearest Neighbors and Automatic Evaluation for Model-specific Quality Estimation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a model-specific, unsupervised QE approach, termed $k$NN-QE, that extracts information from the MT model’s training data using $k$-nearest neighbors. |
Tu Anh Dinh; Tobias Palzer; Jan Niehues; | arxiv-cs.CL | 2024-04-27 |
| 119 | Prefix Text As A Yarn: Eliciting Non-English Alignment in Foundation Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We critically examine this hypothesis within the scope of cross-lingual generation tasks, proposing that the effectiveness of SFT may be constrained by its reliance on prior tokens to guide cross-lingual generation. Based on this crucial insight, and in response to the challenges posed by the costly and limited availability of non-English data for SFT, we introduce a novel training-free alignment method named PreTTY, which employs minimal task-related prior tokens to bridge the foundation LLM and the SFT LLM, achieving comparable performance without training. |
Runzhe Zhan; Xinyi Yang; Derek F. Wong; Lidia S. Chao; Yue Zhang; | arxiv-cs.CL | 2024-04-25 |
| 120 | Translation of Multifaceted Data Without Re-Training of Machine Translation Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, we argue that this practice often overlooks the interrelation between components within the same data point. To address this limitation, we propose a novel MT pipeline that considers the intra-data relation in implementing MT for training data. |
HYEONSEOK MOON et. al. | arxiv-cs.CL | 2024-04-24 |
| 121 | Setting Up The Data Printer with Improved English to Ukrainian Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Examples of task performance expressed in English are abundant, so with a high-quality translation system our community will be enabled to curate datasets faster. To aid this goal, we introduce a recipe to build a translation system using supervised finetuning of a large pretrained language model with a noisy parallel dataset of 3M pairs of Ukrainian and English sentences followed by a second phase of training using 17K examples selected by k-fold perplexity filtering on another dataset of higher quality. |
Yurii Paniv; Dmytro Chaplynskyi; Nikita Trynus; Volodymyr Kyrylov; | arxiv-cs.CL | 2024-04-23 |
| 122 | Automated Multi-Language to English Machine Translation Using Generative Pre-Trained Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we examine using local Generative Pretrained Transformer (GPT) models to perform automated zero shot black-box, sentence wise, multi-natural-language translation into English text. |
Elijah Pelofske; Vincent Urias; Lorie M. Liebrock; | arxiv-cs.CL | 2024-04-22 |
| 123 | Fine-Tuning Large Language Models to Translate: Will A Touch of Noisy Data in Misaligned Languages Suffice? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Traditionally, success in multilingual machine translation can be attributed to three key factors in training data: large volume, diverse translation directions, and high quality. In the current practice of fine-tuning large language models (LLMs) for translation, we revisit the importance of all these factors. |
DAWEI ZHU et. al. | arxiv-cs.CL | 2024-04-22 |
| 124 | From LLM to NMT: Advancing Low-Resource Machine Translation with Claude Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that Claude 3 Opus, a large language model (LLM) released by Anthropic in March 2024, exhibits stronger machine translation competence than other LLMs. |
Maxim Enis; Mark Hopkins; | arxiv-cs.CL | 2024-04-21 |
| 125 | CAILMD-23 at SemEval-2024 Task 1: Multilingual Evaluation of Semantic Textual Relatedness Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The explosive growth of online content demands robust Natural Language Processing (NLP) techniques that can capture nuanced meanings and cultural context across diverse languages. … |
SHARVI ENDAIT et. al. | ArXiv | 2024-04-13 |
| 126 | Multilingual Evaluation of Semantic Textual Relatedness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This work aims to not only showcase our achievements but also inspire further research in multilingual STR, particularly for low-resourced languages. |
SHARVI ENDAIT et. al. | arxiv-cs.CL | 2024-04-13 |
| 127 | Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian As A Case Study Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we revisit state-of-the-art Neural Machine Translation techniques to develop automatic translation systems between German and Bavarian. |
Wan-Hua Her; Udo Kruschwitz; | arxiv-cs.CL | 2024-04-12 |
| 128 | Guiding Large Language Models to Post-Edit Machine Translation with Error Annotations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Machine Translation (MT) remains one of the last NLP tasks where large language models (LLMs) have not yet replaced dedicated supervised systems. This work exploits the complementary strengths of LLMs and supervised MT by guiding LLMs to automatically post-edit MT with external feedback on its quality, derived from Multidimensional Quality Metric (MQM) annotations. |
Dayeon Ki; Marine Carpuat; | arxiv-cs.CL | 2024-04-11 |
| 129 | Charles Translator: A Machine Translation System Between Ukrainian and Czech Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present Charles Translator, a machine translation system between Ukrainian and Czech, developed as part of a society-wide effort to mitigate the impact of the Russian-Ukrainian war on individuals and society. |
MARTIN POPEL et. al. | arxiv-cs.CL | 2024-04-10 |
| 130 | Exploring The Necessity of Visual Modality in Multimodal Machine Translation Using Authentic Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we adhere to the universal multimodal machine translation framework proposed by Tang et al. (2022). |
ZI LONG et. al. | arxiv-cs.CL | 2024-04-09 |
| 131 | Low-Resource Machine Translation Through Retrieval-Augmented LLM Prompting: A Study on The Mambai Language Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study explores the use of large language models (LLMs) for translating English into Mambai, a low-resource Austronesian language spoken in Timor-Leste, with approximately 200,000 native speakers. |
Raphaël Merx; Aso Mahmudi; Katrina Langford; Leo Alberto de Araujo; Ekaterina Vylomova; | arxiv-cs.CL | 2024-04-07 |
| 132 | MaiNLP at SemEval-2024 Task 1: Analyzing Source Language Selection in Cross-Lingual Textual Relatedness Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), on Track C: Cross-lingual. |
Shijia Zhou; Huangyan Shan; Barbara Plank; Robert Litschko; | arxiv-cs.CL | 2024-04-03 |
| 133 | Towards Better Understanding of Cybercrime: The Role of Fine-Tuned LLMs in Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose using fine-tuned Large Language Models (LLM) to generate translations that can accurately capture the nuances of cybercrime language. |
Veronica Valeros; Anna Širokova; Carlos Catania; Sebastian Garcia; | arxiv-cs.CL | 2024-04-02 |
| 134 | Low-resource Neural Machine Translation with Morphological Modeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a framework-solution for modeling complex morphology in low-resource settings. |
Antoine Nzeyimana; | arxiv-cs.CL | 2024-04-02 |
| 135 | Advancing AI with Integrity: Ethical Challenges and Solutions in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We identify and address ethical issues through empirical studies. |
Richard Kimera; Yun-Seon Kim; Heeyoul Choi; | arxiv-cs.CL | 2024-04-01 |
| 136 | Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a syntax-based in-context example selection method for MT, by computing the syntactic similarity between dependency trees using Polynomial Distance. |
Chenming Tang; Zhixiang Wang; Yunfang Wu; | arxiv-cs.CL | 2024-03-28 |
| 137 | A Tulu Resource for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present the first parallel dataset for English-Tulu translation. |
Manu Narayanan; Noëmi Aepli; | arxiv-cs.CL | 2024-03-28 |
| 138 | KazParC: Kazakh Parallel Corpus for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce KazParC, a parallel corpus designed for machine translation across Kazakh, English, Russian, and Turkish. |
Rustem Yeshpanov; Alina Polonskaya; Huseyin Atakan Varol; | arxiv-cs.CL | 2024-03-28 |
| 139 | Improving Vietnamese-English Medical Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we introduce MedEV — a high-quality Vietnamese-English parallel dataset constructed specifically for the medical domain, comprising approximately 360K sentence pairs. |
Nhu Vo; Dat Quoc Nguyen; Dung D. Le; Massimo Piccardi; Wray Buntine; | arxiv-cs.CL | 2024-03-28 |
| 140 | The Impact of Syntactic and Semantic Proximity on Machine Translation with Back-Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Theoretically, however, the method should not work in general. We therefore conduct controlled experiments with artificial languages to determine what properties of languages make back-translation an effective training method, covering lexical, syntactic, and semantic properties. |
Nicolas Guerin; Shane Steinert-Threlkeld; Emmanuel Chemla; | arxiv-cs.CL | 2024-03-26 |
| 141 | M3P: Towards Multimodal Multilingual Translation with Multimodal Prompt Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a framework to leverage the multimodal prompt to guide the Multimodal Multilingual neural Machine Translation (m3P), which aligns the representations of different languages with the same meaning and generates the conditional vision-language memory for translation. |
JIAN YANG et. al. | arxiv-cs.CL | 2024-03-26 |
| 142 | Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we tackle the problem of code-mixed (Hinglish and Bengalish) to English machine translation. |
Kartik Kartik; Sanjana Soni; Anoop Kunchukuttan; Tanmoy Chakraborty; Md Shad Akhtar; | arxiv-cs.CL | 2024-03-25 |
| 143 | Prediction of Translation Techniques for The Translation Process Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In contrast, the process of human-generated translation relies on a wide range of translation techniques, which are crucial for ensuring linguistic adequacy and fluency. This study suggests that these translation techniques could further optimize machine translation if they are automatically identified before being applied to guide the translation process effectively. |
Fan Zhou; Vincent Vandeghinste; | arxiv-cs.CL | 2024-03-21 |
| 144 | Multi-Dimensional Machine Translation Evaluation: Model Evaluation and Resource for Korean Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Previous studies have demonstrated the feasibility of MQM annotation but there are, to our knowledge, no computational models that predict MQM scores for novel texts, due to a lack of resources. In this paper, we address these shortcomings by (a) providing a 1200-sentence MQM evaluation benchmark for the language pair English-Korean and (b) reframing MT evaluation as the multi-task problem of simultaneously predicting several MQM scores using SOTA language models, both in a reference-based MT evaluation setup and a reference-free quality estimation (QE) setup. |
Dojun Park; Sebastian Padó; | arxiv-cs.CL | 2024-03-19 |
| 145 | Enhancing Taiwanese Hokkien Dual Translation By Exploring and Standardizing of Four Writing Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Machine translation focuses mainly on high-resource languages (HRLs), while low-resource languages (LRLs) like Taiwanese Hokkien are relatively under-explored. The study aims to address this gap by developing a dual translation model between Taiwanese Hokkien and both Traditional Mandarin Chinese and English. |
Bo-Han Lu; Yi-Hsuan Lin; En-Shiun Annie Lee; Richard Tzong-Han Tsai; | arxiv-cs.CL | 2024-03-18 |
| 146 | CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we deploy a standard data augmentation methodology by back-translation to a new language translation direction Cantonese-to-English. |
Kung Yin Hong; Lifeng Han; Riza Batista-Navarro; Goran Nenadic; | arxiv-cs.CL | 2024-03-17 |
| 147 | A Novel Paradigm Boosting Translation Capabilities of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents a study on strategies to enhance the translation capabilities of large language models (LLMs) in the context of machine translation (MT) tasks. |
JIAXIN GUO et. al. | arxiv-cs.CL | 2024-03-17 |
| 148 | Scaling Behavior of Machine Translation with Large Language Models Under Prompt Injection Attacks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Their generality, however, opens them up to subversion by end users who may embed into their requests instructions that cause the model to behave in unauthorized and possibly unsafe ways. In this work we study these Prompt Injection Attacks (PIAs) on multiple families of LLMs on a Machine Translation task, focusing on the effects of model size on the attack success rates. |
Zhifan Sun; Antonio Valerio Miceli-Barone; | arxiv-cs.CL | 2024-03-14 |
| 149 | ACT-MNMT Auto-Constriction Turning for Multilingual Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, due to the mixture of multilingual data during the pre-training of LLM, the LLM-based translation models face the off-target issue in both prompt-based methods, including a series of phenomena, namely instruction misunderstanding, translation with wrong language and over-generation. For this issue, this paper introduces an \textbf{\underline{A}}uto-\textbf{\underline{C}}onstriction \textbf{\underline{T}}urning mechanism for \textbf{\underline{M}}ultilingual \textbf{\underline{N}}eural \textbf{\underline{M}}achine \textbf{\underline{T}}ranslation (\model), which is a novel supervised fine-tuning mechanism and orthogonal to the traditional prompt-based methods. |
Shaojie Dai; Xin Liu; Ping Luo; Yue Yu; | arxiv-cs.CL | 2024-03-11 |
| 150 | Enhanced Auto Language Prediction with Dictionary Capsule — A Novel Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper presents a novel Auto Language Prediction Dictionary Capsule (ALPDC) framework for language prediction and machine translation. |
PINNI VENKATA ABHIRAM et. al. | arxiv-cs.CL | 2024-03-09 |
| 151 | Cross-lingual Transfer or Machine Translation? On Data Augmentation for Monolingual Semantic Textual Similarity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we directly compared two data augmentation techniques as potential solutions for monolingual STS: (a) cross-lingual transfer that exploits English resources alone as training data to yield non-English sentence embeddings as zero-shot inference, and (b) machine translation that coverts English data into pseudo non-English training data in advance. |
Sho Hoshino; Akihiko Kato; Soichiro Murakami; Peinan Zhang; | arxiv-cs.CL | 2024-03-08 |
| 152 | Where Does In-context Translation Happen in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we attempt to characterize the region where large language models transition from in-context learners to translation models. |
Suzanna Sia; David Mueller; Kevin Duh; | arxiv-cs.CL | 2024-03-07 |
| 153 | Attempt Towards Stress Transfer in Speech-to-Speech Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present an Indian English-to-Hindi SSMT system that can transfer stress and aim to enhance the overall quality and engagement of educational content. |
Sai Akarsh; Vamshi Raghusimha; Anindita Mondal; Anil Vuppala; | arxiv-cs.CL | 2024-03-06 |
| 154 | BiVert: Bidirectional Vocabulary Evaluation Using Relations for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a bidirectional semantic-based evaluation method designed to assess the sense distance of the translation from the source text. |
Carinne Cherf; Yuval Pinter; | arxiv-cs.CL | 2024-03-06 |
| 155 | GaHealth: An English-Irish Bilingual Corpus of Health Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our study outlines the process used in developing the corpus and empirically demonstrates the benefits of using an in-domain dataset for the health domain. |
Séamus Lankford; Haithem Afli; Órla Ní Loinsigh; Andy Way; | arxiv-cs.CL | 2024-03-06 |
| 156 | General2Specialized LLMs Translation for E-commerce Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Taking e-commerce as an example, the texts usually include amounts of domain-related words and have more grammar problems, which leads to inferior performances of current NMT methods. To address these problems, we collect two domain-related resources, including a set of term pairs (aligned Chinese-English bilingual terms) and a parallel corpus annotated for the e-commerce domain. |
KAIDI CHEN et. al. | arxiv-cs.CL | 2024-03-06 |
| 157 | GaHealth: An English–Irish Bilingual Corpus of Health Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine Translation is a mature technology for many high-resource language pairs. However in the context of low-resource languages, there is a paucity of parallel data datasets … |
Séamus Lankford; Haithem Afli; Orla Ni Loinsigh; Andy Way; | ArXiv | 2024-03-06 |
| 158 | Detecting Concrete Visual Tokens for Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce new methods for detection of visually and contextually relevant (concrete) tokens from source sentences, including detection with natural language processing (NLP), detection with object detection, and a joint detection-verification technique. |
Braeden Bowen; Vipin Vijayan; Scott Grigsby; Timothy Anderson; Jeremy Gwinnup; | arxiv-cs.CL | 2024-03-05 |
| 159 | Adding Multimodal Capabilities to A Text-only Translation Model Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to perform well on both Multi30k and typical text-only datasets, we use a performant text-only machine translation (MT) model as the starting point of our MMT model. |
Vipin Vijayan; Braeden Bowen; Scott Grigsby; Timothy Anderson; Jeremy Gwinnup; | arxiv-cs.CL | 2024-03-05 |
| 160 | The Case for Evaluating Multimodal Translation Models on Text Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Namely, the use of visual information by the MMT model cannot be shown directly from the Multi30k test set results and the sentences in Multi30k are are image captions, i.e., short, descriptive sentences, as opposed to complex sentences that typical text-only machine translation models are evaluated against. Therefore, we propose that MMT models be evaluated using 1) the CoMMuTE evaluation framework, which measures the use of visual information by MMT models, 2) the text-only WMT news translation task test sets, which evaluates translation performance against complex sentences, and 3) the Multi30k test sets, for measuring MMT model performance against a real MMT dataset. |
Vipin Vijayan; Braeden Bowen; Scott Grigsby; Timothy Anderson; Jeremy Gwinnup; | arxiv-cs.CL | 2024-03-05 |
| 161 | Transformers for Low-Resource Languages: Is Féidir Linn! IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The Transformer model is the state-of-the-art in Machine Translation. However and in general and neural translation models often under perform on language pairs with insufficient … |
Séamus Lankford; H. Alfi; Andy Way; | Machine Translation Summit | 2024-03-04 |
| 162 | Machine Translation in The Covid Domain: An English-Irish Case Study for LoResMT 2021 IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Translation models for the specific domain of translating Covid data from English to Irish were developed for the LoResMT 2021 shared task. |
Séamus Lankford; Haithem Afli; Andy Way; | arxiv-cs.CL | 2024-03-02 |
| 163 | EBBS: An Ensemble with Bi-Level Beam Search for Zero-Shot Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our work, we observe that both direct and pivot translations are noisy and achieve less satisfactory performance. We propose EBBS, an ensemble method with a novel bi-level beam search algorithm, where each ensemble component explores its own prediction step by step at the lower level but they are synchronized by a soft voting mechanism at the upper level. |
Yuqiao Wen; Behzad Shayegh; Chenyang Huang; Yanshuai Cao; Lili Mou; | arxiv-cs.CL | 2024-02-29 |
| 164 | A Benchmark for Learning to Translate A New Language from One Grammar Book IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We turn to a field that is explicitly motivated and bottlenecked by a scarcity of web data: low-resource languages. In this paper, we introduce MTOB (Machine Translation from One Book), a benchmark for learning to translate between English and Kalamang—a language with less than 200 speakers and therefore virtually no presence on the web—using several hundred pages of field linguistics reference materials. |
Garrett Tanzer; Mirac Suzgun; Eline Visser; Dan Jurafsky; Luke Melas-Kyriazi; | iclr | 2024-02-26 |
| 165 | MT-Ranker: Reference-free Machine Translation Evaluation By Inter-system Ranking Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we formulate the reference-free MT evaluation into a pairwise ranking problem. |
Ibraheem Muhammad Moosa; Rui Zhang; Wenpeng Yin; | iclr | 2024-02-26 |
| 166 | TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Importantly, feeding back such error information into the LLMs can lead to self-refinement and result in improved translation performance. Motivated by these insights, we introduce a systematic LLM-based self-refinement translation framework, named \textbf{TEaR}, which stands for \textbf{T}ranslate, \textbf{E}stimate, \textbf{a}nd \textbf{R}efine, marking a significant step forward in this direction. |
ZHAOPENG FENG et. al. | arxiv-cs.CL | 2024-02-26 |
| 167 | A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we propose a novel fine-tuning approach for LLMs that is specifically designed for the translation task, eliminating the need for the abundant parallel data that traditional translation models usually depend on. |
Haoran Xu; Young Jin Kim; Amr Sharaf; Hany Hassan Awadalla; | iclr | 2024-02-26 |
| 168 | An Interpretable Error Correction Method for Enhancing Code-to-code Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Moreover, researchers frequently invest substantial time and computational resources in retraining models, yet the improvement in translation accuracy is quite limited. To address these issues, we introduce a novel approach, $k\text{NN-ECD}$, which combines $k$-nearest-neighbor search with a key-value error correction datastore to overwrite the wrong translations of TransCoder-ST. |
Min Xue; Artur Andrzejak; Marla Leuther; | iclr | 2024-02-26 |
| 169 | TMT: Tri-Modal Translation Between Speech, Image, and Text By Processing Different Modalities As Different Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a novel Tri-Modal Translation (TMT) model that translates between arbitrary modalities spanning speech, image, and text. |
MINSU KIM et. al. | arxiv-cs.CL | 2024-02-25 |
| 170 | Direct Punjabi to English Speech Translation Using Discrete Units Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With a motive to contribute towards speech translation research for low-resource languages, our work presents a direct speech-to-speech translation model for one of the Indic languages called Punjabi to English. |
Prabhjot Kaur; L. Andrew M. Bush; Weisong Shi; | arxiv-cs.CL | 2024-02-24 |
| 171 | Could We Have Had Better Multilingual LLMs If English Was Not The Central Language? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large Language Models (LLMs) demonstrate strong machine translation capabilities on languages they are trained on. |
Ryandito Diandaru; Lucky Susanto; Zilu Tang; Ayu Purwarianti; Derry Wijaya; | arxiv-cs.CL | 2024-02-21 |
| 172 | Bangla AI: A Framework for Machine Translation Utilizing Large Language Models for Ethnic Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The paper outlines a theoretical framework elucidating the integration of LLM and MMT into the news searching and translation processes for ethnic media. |
MD Ashraful Goni; Fahad Mostafa; Kerk F. Kee; | arxiv-cs.CL | 2024-02-21 |
| 173 | GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite numerous studies on gender bias in translations into English from weakly gendered-languages, there are no benchmarks for evaluating this phenomenon or for assessing mitigation strategies. To address this gap, we introduce GATE X-E, an extension to the GATE (Rarrick et al., 2023) corpus, that consists of human translations from Turkish, Hungarian, Finnish, and Persian into English. |
Spencer Rarrick; Ranjita Naik; Sundar Poudel; Vishal Chowdhary; | arxiv-cs.CL | 2024-02-21 |
| 174 | SiLLM: Large Language Models for Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose SiLLM, which delegates the two sub-tasks to separate agents, thereby incorporating LLM into SiMT. |
Shoutao Guo; Shaolei Zhang; Zhengrui Ma; Min Zhang; Yang Feng; | arxiv-cs.CL | 2024-02-20 |
| 175 | UMBCLU at SemEval-2024 Task 1A and 1C: Semantic Textual Relatedness with and Without Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Large language models (LLMs) have shown impressive performance on several natural language understanding tasks such as multilingual machine translation (MMT), semantic similarity (STS), and encoding sentence embeddings. Using a combination of LLMs that perform well on these tasks, we developed two STR models, $\textit{TranSem}$ and $\textit{FineSem}$, for the supervised and cross-lingual settings. |
Shubhashis Roy Dipta; Sai Vallurupalli; | arxiv-cs.CL | 2024-02-20 |
| 176 | UMBCLU at SemEval-2024 Task 1: Semantic Textual Relatedness with and Without Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The aim of SemEval-2024 Task 1, “Semantic Textual Relatedness for African and Asian Languages” is to develop models for identifying semantic textual relatedness (STR) between two … |
Shubhashis Roy Dipta; Sai Vallurupalli; | Proceedings of the 18th International Workshop on Semantic … | 2024-02-20 |
| 177 | Enhanced Hallucination Detection in Neural Machine Translation Through Simple Detector Aggregation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Previous research works have identified that detectors exhibit complementary performance different detectors excel at detecting different types of hallucinations. In this paper, we propose to address the limitations of individual detectors by combining them and introducing a straightforward method for aggregating multiple detectors. |
Anas Himmi; Guillaume Staerman; Marine Picot; Pierre Colombo; Nuno M. Guerreiro; | arxiv-cs.CL | 2024-02-20 |
| 178 | Advancing Translation Preference Modeling with RLHF: A Step Towards Cost-Effective Solution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we explore leveraging reinforcement learning with human feedback (\textit{RLHF}) to improve translation quality. |
NUO XU et. al. | arxiv-cs.CL | 2024-02-18 |
| 179 | Rethinking Human-like Translation Strategy: Integrating Drift-Diffusion Model with Large Language Models for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, prior work on LLM-based machine translation has mainly focused on better utilizing training data, demonstrations, or pre-defined and universal knowledge to improve performance, with a lack of consideration of decision-making like human translators. In this paper, we incorporate Thinker with the Drift-Diffusion Model (Thinker-DDM) to address this issue. |
HONGBIN NA et. al. | arxiv-cs.CL | 2024-02-16 |
| 180 | Unsupervised Sign Language Translation and Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a sliding window method to address the issues of aligning variable-length text with video sequences. |
ZHENGSHENG GUO et. al. | arxiv-cs.CL | 2024-02-12 |
| 181 | GenTranslate: Large Language Models Are Generative Multilingual Speech and Machine Translators Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new generative paradigm for translation tasks, namely GenTranslate, which builds upon LLMs to generate better results from the diverse translation versions in N-best list. |
YUCHEN HU et. al. | arxiv-cs.CL | 2024-02-10 |
| 182 | A Prompt Response to The Demand for Automatic Gender-Neutral Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For such a scenario, large language models offer hitherto unforeseen possibilities, as they come with the distinct advantage of being versatile in various (sub)tasks when provided with explicit instructions. In this paper, we explore this potential to automate GNT by comparing MT with the popular GPT-4 model. |
Beatrice Savoldi; Andrea Piergentili; Dennis Fucci; Matteo Negri; Luisa Bentivogli; | arxiv-cs.CL | 2024-02-08 |
| 183 | TransLLaMa: LLM-based Simultaneous Translation System Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study demonstrates that, after fine-tuning on a small dataset comprising causally aligned source and target sentence pairs, a pre-trained open-source LLM can control input segmentation directly by generating a special wait token. |
Roman Koshkin; Katsuhito Sudoh; Satoshi Nakamura; | arxiv-cs.CL | 2024-02-07 |
| 184 | Error Analysis of Pretrained Language Models (PLMs) in English-to-Arabic Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View |
H. Al-Khalifa; Khaloud Al-Khalefah; Hesham Haroon; | Hum. Centric Intell. Syst. | 2024-02-05 |
| 185 | A Morphologically-Aware Dictionary-based Data Augmentation Technique for Machine Translation of Under-Represented Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose strategies to synthesize parallel data relying on morpho-syntactic information and using bilingual lexicons along with a small amount of seed parallel data. |
Md Mahfuz Ibn Alam; Sina Ahmadi; Antonios Anastasopoulos; | arxiv-cs.CL | 2024-02-02 |
| 186 | Neural Machine Translation for Malayalam Paraphrase Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study explores four methods of generating paraphrases in Malayalam, utilizing resources available for English paraphrasing and pre-trained Neural Machine Translation (NMT) models. |
Christeena Varghese; Sergey Koshelev; Ivan P. Yamshchikov; | arxiv-cs.CL | 2024-01-31 |
| 187 | Massively Multilingual Text Translation For Low-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We attempt to leverage translation resources from rich-resource languages to efficiently produce best possible translation quality for well known texts, which are available in multiple languages, in a new, low-resource language. |
Zhong Zhou; | arxiv-cs.CL | 2024-01-29 |
| 188 | Non-Fluent Synthetic Target-Language Data Improve Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: These approaches work under the assumption that non-fluent target-side synthetic training samples can be harmful and may deteriorate translation performance. Even so, in this paper we demonstrate that synthetic training samples with non-fluent target sentences can improve translation performance if they are used in a multilingual machine translation framework as if they were sentences in another language. |
Víctor M. Sánchez-Cartagena; Miquel Esplà-Gomis; Juan Antonio Pérez-Ortiz; Felipe Sánchez-Martínez; | arxiv-cs.CL | 2024-01-29 |
| 189 | MultiMUC: Multilingual Template Filling on MUC-4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce MultiMUC, the first multilingual parallel corpus for template filling, comprising translations of the classic MUC-4 template filling benchmark into five languages: Arabic, Chinese, Farsi, Korean, and Russian. |
WILLIAM GANTT et. al. | arxiv-cs.CL | 2024-01-29 |
| 190 | Language Modelling Approaches to Adaptive Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models (LLMs) have recently shown interesting capabilities of in-context learning, where they learn to replicate certain input-output text generation patterns, without further fine-tuning. Such capabilities have opened new horizons for domain-specific data augmentation and real-time adaptive MT. This work attempts to address two main relevant questions: 1) in scenarios involving human interaction and continuous feedback, can we employ language models to improve the quality of adaptive MT at inference time? |
Yasmin Moslem; | arxiv-cs.CL | 2024-01-25 |
| 191 | Misgendering and Assuming Gender in Machine Translation When Working with Low-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This chapter focuses on gender-related errors in machine translation (MT) in the context of low-resource languages. |
Sourojit Ghosh; Srishti Chatterjee; | arxiv-cs.CL | 2024-01-23 |
| 192 | An Empirical Study of In-context Learning in LLMs for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent interest has surged in employing Large Language Models (LLMs) for machine translation (MT) via in-context learning (ICL) (Vilar et al., 2023). |
Pranjal A. Chitale; Jay Gala; Raj Dabre; | arxiv-cs.CL | 2024-01-22 |
| 193 | How Far Can 100 Samples Go? Unlocking Overall Zero-Shot Multilingual Translation Via Tiny Multi-Parallel Data Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we show that for an English-centric model, surprisingly large zero-shot improvements can be achieved by simply fine-tuning with a very small amount of multi-parallel data. |
Di Wu; Shaomu Tan; Yan Meng; David Stap; Christof Monz; | arxiv-cs.CL | 2024-01-22 |
| 194 | Gender Bias in Machine Translation and The Era of Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This chapter examines the role of Machine Translation in perpetuating gender bias, highlighting the challenges posed by cross-linguistic settings and statistical dependencies. |
Eva Vanmassenhove; | arxiv-cs.CL | 2024-01-18 |
| 195 | Gradable ChatGPT Translation Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Accordingly, this paper proposes a generic taxonomy, which defines gradable translation prompts in terms of expression type, translation style, POS information and explicit statement, thus facilitating the construction of prompts endowed with distinct attributes tailored for various translation tasks. |
Hui Jiao; Bei Peng; Lu Zong; Xiaojun Zhang; Xinwei Li; | arxiv-cs.CL | 2024-01-18 |
| 196 | Machine Translation with Large Language Models: Prompt Engineering for Persian, English, and Russian Directions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Generative large language models (LLMs) have demonstrated exceptional proficiency in various natural language processing (NLP) tasks, including machine translation, question … |
Nooshin Pourkamali; Shler Ebrahim Sharifi; | ArXiv | 2024-01-16 |
| 197 | A Novel Approach for Automatic Program Repair Using Round-Trip Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes bypassing the fine-tuning step and using Round-Trip Translation (RTT): translation of code from one programming language to another programming or natural language, and back. |
Fernando Vallecillos Ruiz; Anastasiia Grishina; Max Hort; Leon Moonen; | arxiv-cs.SE | 2024-01-15 |
| 198 | Enhancing Document-level Translation of Large Language Model Via Translation Mixed-instructions Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To address the issue, we propose an approach that combines sentence-level and document-level translation instructions of varying lengths to fine-tune LLMs. |
Yachao Li; Junhui Li; Jing Jiang; Min Zhang; | arxiv-cs.CL | 2024-01-15 |
| 199 | An Approach for Mistranslation Removal from Popular Dataset for Indic MT Task Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Hence, the MT systems built using this dataset cannot perform to their usual potential. In this paper, we propose an algorithm to remove mistranslations from the training corpus and evaluate its performance and efficiency. |
Sudhansu Bala Das; Leo Raphael Rodrigues; Tapas Kumar Mishra; Bidyut Kr. Patra; | arxiv-cs.CL | 2024-01-12 |
| 200 | Adapting Large Language Models for Document-Level Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Our results show that specialized models can sometimes surpass GPT-4 in translation performance but still face issues like off-target translation due to error propagation in decoding. We provide an in-depth analysis of these LLMs tailored for DocMT, examining translation errors, discourse phenomena, training strategies, the scaling law of parallel documents, recent test set evaluations, and zero-shot crosslingual transfer. |
Minghao Wu; Thuy-Trang Vu; Lizhen Qu; George Foster; Gholamreza Haffari; | arxiv-cs.CL | 2024-01-12 |
| 201 | MiTTenS: A Dataset for Evaluating Gender Mistranslation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Translation systems, including foundation models capable of translation, can produce errors that result in gender mistranslation, and such errors can be especially harmful. To measure the extent of such potential harms when translating into and out of English, we introduce a dataset, MiTTenS, covering 26 languages from a variety of language families and scripts, including several traditionally under-represented in digital resources. |
Kevin Robinson; Sneha Kudugunta; Romina Stella; Sunipa Dev; Jasmijn Bastings; | arxiv-cs.CL | 2024-01-12 |
| 202 | Machine Translation Models Are Zero-Shot Detectors of Translation Direction Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we explore an unsupervised approach to translation direction detection based on the simple hypothesis that $p(\text{translation}|\text{original})>p(\text{original}|\text{translation})$, motivated by the well-known simplification effect in translationese or machine-translationese. |
Michelle Wastl; Jannis Vamvas; Rico Sennrich; | arxiv-cs.CL | 2024-01-12 |
| 203 | Lost in The Source Language: How Large Language Models Evaluate The Quality of Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study investigates how Large Language Models (LLMs) leverage source and reference data in machine translation evaluation task, aiming to better understand the mechanisms behind their remarkable performance in this task. |
XU HUANG et. al. | arxiv-cs.CL | 2024-01-12 |
| 204 | Towards Boosting Many-to-Many Multilingual Machine Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on boosting many-to-many multilingual translation of LLMs with an emphasis on zero-shot translation directions. |
Pengzhi Gao; Zhongjun He; Hua Wu; Haifeng Wang; | arxiv-cs.CL | 2024-01-11 |
| 205 | Tuning LLMs with Contrastive Alignment Instructions for Machine Translation in Unseen, Low-resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article introduces contrastive alignment instructions (AlignInstruct) to address two challenges in machine translation (MT) on large language models (LLMs). |
Zhuoyuan Mao; Yen Yu; | arxiv-cs.CL | 2024-01-11 |
| 206 | POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Probability-driven Meta-graph Prompter (POMP), a novel approach employing a dynamic, sampling-based graph of multiple auxiliary languages to enhance LLMs’ translation capabilities for LRLs. |
SHILONG PAN et. al. | arxiv-cs.CL | 2024-01-10 |
| 207 | Convergences and Divergences Between Automatic Assessment and Human Evaluation: Insights from Comparing ChatGPT-Generated Translation and Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Large language models have demonstrated parallel and even superior translation performance compared to neural machine translation (NMT) systems. |
Zhaokun Jiang; Ziyin Zhang; | arxiv-cs.CL | 2024-01-10 |
| 208 | Aligning Translation-Specific Understanding to General Understanding in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To align the translation-specific understanding to the general one, we propose a novel translation process xIoD (Cross-Lingual Interpretation of Difficult words), explicitly incorporating the general understanding on the content incurring inconsistent understanding to guide the translation. |
YICHONG HUANG et. al. | arxiv-cs.CL | 2024-01-10 |
| 209 | LAMPAT: Low-Rank Adaption for Multilingual Paraphrasing Using Adversarial Training Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To mitigate that problem, we proposed the first unsupervised multilingual paraphrasing model, LAMPAT ($\textbf{L}$ow-rank $\textbf{A}$daptation for $\textbf{M}$ultilingual $\textbf{P}$araphrasing using $\textbf{A}$dversarial $\textbf{T}$raining), by which monolingual dataset is sufficient enough to generate a human-like and diverse sentence. |
Khoi M. Le; Trinh Pham; Tho Quan; Anh Tuan Luu; | arxiv-cs.CL | 2024-01-08 |
| 210 | MirrorDiffusion: Stabilizing Diffusion Process in Zero-shot Image Translation By Prompts Redescription and Beyond Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To make reconstruction explicit, we propose a prompt redescription strategy to realize a mirror effect between the source and reconstructed image in the diffusion model (MirrorDiffusion). |
Yupei Lin; Xiaoyu Xian; Yukai Shi; Liang Lin; | arxiv-cs.CV | 2024-01-06 |
| 211 | Improving LLM-based Machine Translation with Systematic Self-Correction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large Language Models (LLMs) have achieved impressive results in Machine Translation (MT). However, careful evaluations by human reveal that the translations produced by LLMs … |
ZHAOPENG FENG et. al. | ArXiv | 2024-01-01 |
| 212 | Mediapi-RGB: Enabling Technological Breakthroughs in French Sign Language (LSF) Research Through An Extensive Video-Text Corpus Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: We introduce Mediapi-RGB, a new dataset of French Sign Language (LSF) along with the first LSF-to-French machine translation model. With 86 hours of video, it the largest LSF … |
YANIS OUAKRIM et. al. | VISIGRAPP : VISAPP | 2024-01-01 |
| 213 | CLAD-ST: Contrastive Learning with Adversarial Data for Robust Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We address this robustness problem in downstream MT models by forcing the MT encoder to bring the representations of a noisy input closer to its clean version in the semantic space. This is achieved by introducing a contrastive learning method that leverages adversarial examples in the form of ASR outputs paired with their corresponding human transcripts to optimize the network parameters. |
Sathish Indurthi; Shamil Chollampatt; Ravi Agrawal; Marco Turchi; | emnlp | 2023-12-22 |
| 214 | An Empirical Study of Translation Hypothesis Ensembling with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate how hypothesis ensembling can improve the quality of the generated text for the specific problem of LLM-based machine translation. |
Ant�nio Farinhas; Jos� de Souza; Andre Martins; | emnlp | 2023-12-22 |
| 215 | Program Translation Via Code Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we propose a novel model called Code Distillation (CoDist) whereby we capture the semantic and structural equivalence of code in a language agnostic intermediate representation. |
YUFAN HUANG et. al. | emnlp | 2023-12-22 |
| 216 | Towards A Better Understanding of Variations in Zero-Shot Neural Machine Translation Performance Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Through systematic experimentation, spanning 1,560 language directions across 40 languages, we identify three key factors contributing to high variations in ZS NMT performance: 1) target-side translation quality, 2) vocabulary overlap, and 3) linguistic properties. |
Shaomu Tan; Christof Monz; | emnlp | 2023-12-22 |
| 217 | Revisiting Machine Translation for Cross-lingual Classification IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that, by using a stronger MT system and mitigating the mismatch between training on original text and running inference on machine translated text, translate-test can do substantially better than previously assumed. |
Mikel Artetxe; Vedanuj Goswami; Shruti Bhosale; Angela Fan; Luke Zettlemoyer; | emnlp | 2023-12-22 |
| 218 | MT2: Towards A Multi-Task Machine Translation Model with Translation-Specific In-Context Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Most of the previous work uses separate models or methods to solve these tasks, which is not conducive to knowledge transfer of different tasks and increases the complexity of system construction. In this work, we explore the potential of pre-trained language model in machine translation tasks and propose a Multi-Task Machine Translation (MT2) model to integrate these translation tasks. |
CHUNYOU LI et. al. | emnlp | 2023-12-22 |
| 219 | MMNMT: Modularizing Multilingual Neural Machine Translation with Flexibly Assembled MoE and Dense Blocks Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a modularized MNMT framework that is able to flexibly assemble dense and MoE-based sparse modules to achieve the best of both worlds. |
SHANGJIE LI et. al. | emnlp | 2023-12-22 |
| 220 | Continual Learning for Multilingual Neural Machine Translation Via Dual Importance-based Model Division Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To achieve this, the existing methods primarily focus on preventing catastrophic forgetting by making compromises between the original and new language pairs, leading to sub-optimal performance on both translation tasks. To mitigate this problem, we propose a dual importance-based model division method to divide the model parameters into two parts and separately model the translation of the original and new tasks. |
JUNPENG LIU et. al. | emnlp | 2023-12-22 |
| 221 | A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In MT, this might lead to misgendered translations, resulting, among other harms, in the perpetuation of stereotypes and prejudices. In this work, we address this gap by investigating whether and to what extent such models exhibit gender bias in machine translation and how we can mitigate it. |
Giuseppe Attanasio; Flor Plaza del Arco; Debora Nozza; Anne Lauscher; | emnlp | 2023-12-22 |
| 222 | Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with The GeNTE Corpus Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Based on GeNTE, we then overview existing reference-based evaluation approaches, highlight their limits, and propose a reference-free method more suitable to assess gender-neutral translation. |
Andrea Piergentili; Beatrice Savoldi; Dennis Fucci; Matteo Negri; Luisa Bentivogli; | emnlp | 2023-12-22 |
| 223 | Crossing The Threshold: Idiomatic Machine Translation Through Retrieval Augmentation and Loss Weighting Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To improve translation of natural idioms, we introduce two straightforward yet effective techniques: the strategic upweighting of training loss on potentially idiomatic sentences, and using retrieval-augmented models. |
Emmy Liu; Aditi Chaudhary; Graham Neubig; | emnlp | 2023-12-22 |
| 224 | HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we release an annotated dataset for the hallucination and omission phenomena covering 18 translation directions with varying resource levels and scripts. |
DAVID DALE et. al. | emnlp | 2023-12-22 |
| 225 | Learn and Consolidate: Continual Adaptation for Zero-Shot and Multilingual Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we propose a two-stage approach that encourages original models to acquire language-agnostic multilingual representations from new data, and preserves the model architecture without introducing parameters. |
Kaiyu Huang; Peng Li; Junpeng Liu; Maosong Sun; Yang Liu; | emnlp | 2023-12-22 |
| 226 | PromptST: Abstract Prompt Learning for End-to-End Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we take the first step toward understanding the fusion of speech and text features in S2T model. |
TENGFEI YU et. al. | emnlp | 2023-12-22 |
| 227 | DecoMT: Decomposed Prompting for Machine Translation Between Related Languages Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce DecoMT, a novel approach of few-shot prompting that decomposes the translation process into a sequence of word chunk translations. |
Ratish Puduppully; Anoop Kunchukuttan; Raj Dabre; Ai Ti Aw; Nancy Chen; | emnlp | 2023-12-22 |
| 228 | Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, when it comes to non-English languages, the quantity and quality of textual information are comparatively scarce. To address this issue, we introduce the novel task of automatic Knowledge Graph Completion (KGE) and perform a thorough investigation on bridging the gap in both the quantity and quality of textual information between English and non-English languages. |
SIMONE CONIA et. al. | emnlp | 2023-12-22 |
| 229 | PROSE: A Pronoun Omission Solution for Chinese-English Spoken Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To alleviate the negative impact introduced by pro-drop, we propose Mention-Aware Semantic Augmentation, a novel approach that leverages the semantic embedding of dropped pronouns to augment training pairs. |
Ke Wang; Xiutian Zhao; Yanghui Li; Wei Peng; | emnlp | 2023-12-22 |
| 230 | On The Use of Metaphor Translation in Psychiatry Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Now, metaphor has been shown to be paramount in both identifying individuals struggling with mental problems and helping those individuals understand and communicate their experiences. Therefore, this paper aims to survey the potential of Machine Translation for providing equitable psychiatric healthcare and highlights the need for further research on the transferability of existing machine and metaphor translation research in the domain of psychiatry. |
Lois Wong; | arxiv-cs.CL | 2023-12-22 |
| 231 | Challenges in Context-Aware Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate and present several core challenges that impede progress within the field, relating to discourse phenomena, context usage, model architectures, and document-level evaluation. |
Linghao Jin; Jacqueline He; Jonathan May; Xuezhe Ma; | emnlp | 2023-12-22 |
| 232 | Multilingual K-Nearest-Neighbor Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these improvements have been limited to high-resource language pairs, with large datastores, and remain a challenge for low-resource languages. In this paper, we address this issue by combining representations from multiple languages into a single datastore. |
David Stap; Christof Monz; | emnlp | 2023-12-22 |
| 233 | Video-Helpful Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce EVA (Extensive training set and Video-helpful evaluation set for Ambiguous subtitles translation), an MMT dataset containing 852k Japanese-English parallel subtitle pairs, 520k Chinese-English parallel subtitle pairs, and corresponding video clips collected from movies and TV episodes. |
Yihang Li; Shuichiro Shimizu; Chenhui Chu; Sadao Kurohashi; Wei Li; | emnlp | 2023-12-22 |
| 234 | Document-Level Machine Translation with Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The study focuses on three aspects: 1) Effects of Context-Aware Prompts, where we investigate the impact of different prompts on document-level translation quality and discourse phenomena; 2) Comparison of Translation Models, where we compare the translation performance of ChatGPT with commercial MT systems and advanced document-level MT methods; 3) Analysis of Discourse Modelling Abilities, where we further probe discourse knowledge encoded in LLMs and shed light on impacts of training techniques on discourse modeling. |
LONGYUE WANG et. al. | emnlp | 2023-12-22 |
| 235 | Exploring Discourse Structure in Document-level Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a more sound paragraph-to-paragraph translation mode and explore whether discourse structure can improve DocMT. |
Xinyu Hu; Xiaojun Wan; | emnlp | 2023-12-22 |
| 236 | Contextual Code Switching for Machine Translation Using Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present an extensive study on the code switching task specifically for the machine translation task comparing multiple LLMs. |
Arshad Kaji; Manan Shah; | arxiv-cs.CL | 2023-12-20 |
| 237 | An Empirical Study of Unsupervised Neural Machine Translation: Analyzing NMT Output, Model’s Behavior and Sentences’ Contribution Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We focus on three very diverse languages, French, Gujarati, and Kazakh, and train bilingual NMT models, to and from English, with various levels of supervision, in high- and low- resource setups, measure quality of the NMT output and compare the generated sequences’ word order and semantic similarity to source and reference sentences. |
Isidora Chara Tourni; Derry Wijaya; | arxiv-cs.CL | 2023-12-19 |
| 238 | Fine-tuning Large Language Models for Adaptive Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents the outcomes of fine-tuning Mistral 7B, a general-purpose large language model (LLM), for adaptive machine translation (MT). |
Yasmin Moslem; Rejwanul Haque; Andy Way; | arxiv-cs.CL | 2023-12-19 |
| 239 | Predicting Human Translation Difficulty with Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that surprisal and attention are complementary predictors of translation difficulty, and that surprisal derived from a NMT model is the single most successful predictor of production duration. |
Zheng Wei Lim; Ekaterina Vylomova; Charles Kemp; Trevor Cohn; | arxiv-cs.CL | 2023-12-18 |
| 240 | Overview of MTIL Track at FIRE 2023: Machine Translation for Indian Languages Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The objective of the MTIL track in FIRE 2023 was to encourage the development of Indian Language to Indian Language (IL-IL) Neural Machine Translation models. The languages … |
SURUPENDU GANGOPADHYAY et. al. | Proceedings of the 15th Annual Meeting of the Forum for … | 2023-12-15 |
| 241 | Neural Machine Translation of Clinical Text: An Empirical Investigation Into Multilingual Pre-Trained Language Models and Transfer-Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We conduct investigations on clinical text machine translation by examining multilingual neural network models using deep learning such as Transformer based structures. |
LIFENG HAN et. al. | arxiv-cs.CL | 2023-12-12 |
| 242 | Converting Epics/Stories Into Pseudocode Using Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: With this research paper, we aim to present a methodology to generate pseudocode from a given agile user story of small functionalities so as to reduce the overall time spent on the industrial project. |
Gaurav Kolhatkar; Akshit Madan; Nidhi Kowtal; Satyajit Roy; Sheetal Sonawane; | arxiv-cs.CL | 2023-12-08 |
| 243 | Making Translators Privacy-aware on The User’s Side Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose PRISM to enable users of machine translation systems to preserve the privacy of data on their own initiative. |
Ryoma Sato; | arxiv-cs.CR | 2023-12-07 |
| 244 | Improving Neural Machine Translation By Multi-Knowledge Integration with Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we focus on how to integrate multi-knowledge, multiple types of knowledge, into NMT models to enhance the performance with prompting. |
Ke Wang; Jun Xie; Yuqi Zhang; Yu Zhao; | arxiv-cs.CL | 2023-12-07 |
| 245 | First Attempt at Building Parallel Corpora for Machine Translation of Northeast India’s Very Low-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents the creation of initial bilingual corpora for thirteen very low-resource languages of India, all from Northeast India. |
Atnafu Lambebo Tonja; Melkamu Mersha; Ananya Kalita; Olga Kolesnikova; Jugal Kalita; | arxiv-cs.CL | 2023-12-07 |
| 246 | Efficient Monotonic Multihead Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce the Efficient Monotonic Multihead Attention (EMMA), a state-of-the-art simultaneous translation model with numerically-stable and unbiased monotonic alignment estimation. |
Xutai Ma; Anna Sun; Siqi Ouyang; Hirofumi Inaguma; Paden Tomasello; | arxiv-cs.CL | 2023-12-07 |
| 247 | Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we address key challenges facing LLMs fine-tuned for SimulMT, validate classical SimulMT concepts and practices in the context of LLMs, explore adapting LLMs that are fine-tuned for NMT to the task of SimulMT, and introduce Simul-LLM, the first open-source fine-tuning and evaluation pipeline development framework for LLMs focused on SimulMT. |
Victor Agostinelli; Max Wild; Matthew Raffel; Kazi Ahmed Asif Fuad; Lizhong Chen; | arxiv-cs.CL | 2023-12-07 |
| 248 | End-to-End Speech-to-Text Translation: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: As a result, researchers have been exploring end-to-end (E2E) models for ST translation. |
Nivedita Sethiya; Chandresh Kumar Maurya; | arxiv-cs.CL | 2023-12-02 |
| 249 | Quick Back-Translation for Unsupervised Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose a two-for-one improvement to Transformer back-translation: Quick Back-Translation (QBT). |
Benjamin Brimacombe; Jiawei Zhou; | arxiv-cs.CL | 2023-12-01 |
| 250 | Women Are Beautiful, Men Are Leaders: Gender Stereotypes in Machine Translation and Language Modeling Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present GEST — a new dataset for measuring gender-stereotypical reasoning in masked LMs and English-to-X machine translation systems. |
Matúš Pikuliak; Andrea Hrckova; Stefan Oresko; Marián Šimko; | arxiv-cs.CL | 2023-11-30 |
| 251 | Relevance-guided Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an explainability-based training approach for NMT, applied in Unsupervised and Supervised model training, for translation of three languages of varying resources, French, Gujarati, Kazakh, to and from English. |
Isidora Chara Tourni; Derry Wijaya; | arxiv-cs.CL | 2023-11-30 |
| 252 | INarIG: Iterative Non-autoregressive Instruct Generation Model For Word-Level Auto Completion Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose the INarIG (Iterative Non-autoregressive Instruct Generation) model, which constructs the human typed sequence into Instruction Unit and employs iterative decoding with subwords to fully utilize input information given in the task. |
HENGCHAO SHANG et. al. | arxiv-cs.CL | 2023-11-29 |
| 253 | AdaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: The advent of Multilingual Language Models (MLLMs) and Large Language Models (LLMs) has spawned innovation in many areas of natural language processing. Despite the exciting … |
Séamus Lankford; Haithem Afli; Andy Way; | Inf. | 2023-11-29 |
| 254 | A Benchmark for Evaluating Machine Translation Metrics on Dialects Without Standard Orthography Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we evaluate how robust metrics are to non-standardized dialects, i.e. spelling differences in language varieties that do not have a standard orthography. |
Noëmi Aepli; Chantal Amrhein; Florian Schottmann; Rico Sennrich; | arxiv-cs.CL | 2023-11-28 |
| 255 | Reducing Gender Bias in Machine Translation Through Counterfactual Data Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We also propose a novel domain-adaptation technique that leverages in-domain data created with the counterfactual data generation techniques proposed by Zmigrod et al. (2019) to further improve accuracy on the WinoMT challenge test set without significant loss in translation quality. We show its effectiveness in NMT systems from English into three morphologically rich languages French, Spanish, and Italian. |
Ranjita Naik; Spencer Rarrick; Vishal Chowdhary; | arxiv-cs.CL | 2023-11-27 |
| 256 | Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, when it comes to non-English languages, the quantity and quality of textual information are comparatively scarce. To address this issue, we introduce the novel task of automatic Knowledge Graph Enhancement (KGE) and perform a thorough investigation on bridging the gap in both the quantity and quality of textual information between English and non-English languages. |
SIMONE CONIA et. al. | arxiv-cs.AI | 2023-11-27 |
| 257 | Improving Word Sense Disambiguation in Neural Machine Translation with Salient Document Context Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a simple and scalable approach to resolve translation ambiguity by incorporating a small amount of extra-sentential context in neural \mt. Our approach requires no sense annotation and no change to standard model architectures. |
Elijah Rippeth; Marine Carpuat; Kevin Duh; Matt Post; | arxiv-cs.CL | 2023-11-26 |
| 258 | Machine Translation to Control Formality Features in The Target Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: When a language translation technique is used to translate from a source language that does not pertain the formality (e.g. English) to a target language that does, there is a missing information on formality that could be a challenge in producing an accurate outcome. This research explores how this issue should be resolved when machine learning methods are used to translate from English to languages with formality, using Hindi as the example data. |
Harshita Tyagi; Prashasta Jung; Hyowon Lee; | arxiv-cs.CL | 2023-11-22 |
| 259 | Context-aware Neural Machine Translation for English-Japanese Business Scene Dialogues Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we explore how context-awareness can improve the performance of the current Neural Machine Translation (NMT) models for English-Japanese business dialogues translation, and what kind of context provides meaningful information to improve translation. |
Sumire Honda; Patrick Fernandes; Chrysoula Zerva; | arxiv-cs.CL | 2023-11-20 |
| 260 | Vashantor: A Large-scale Multilingual Benchmark Dataset for Automated Translation of Bangla Regional Dialects to Bangla Language Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Despite extensive study into translating Bangla to English, English to Bangla, and Banglish to Bangla in the past, there has been a noticeable gap in translating Bangla regional dialects into standard Bangla. In this study, we set out to fill this gap by creating a collection of 32,500 sentences, encompassing Bangla, Banglish, and English, representing five regional Bangla dialects. |
FATEMA TUJ JOHORA FARIA et. al. | arxiv-cs.CL | 2023-11-18 |
| 261 | SentAlign: Accurate and Scalable Sentence Alignment Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs. |
Steinþór Steingrímsson; Hrafn Loftsson; Andy Way; | arxiv-cs.CL | 2023-11-15 |
| 262 | Evaluating Gender Bias in The Translation of Gender-Neutral Languages Into English Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Despite numerous studies into gender bias in translations from gender-neutral languages such as Turkish into more strongly gendered languages like English, there are no benchmarks for evaluating this phenomenon or for assessing mitigation strategies. To address this gap, we introduce GATE X-E, an extension to the GATE (Rarrick et al., 2023) corpus, that consists of human translations from Turkish, Hungarian, Finnish, and Persian into English. |
Spencer Rarrick; Ranjita Naik; Sundar Poudel; Vishal Chowdhary; | arxiv-cs.CL | 2023-11-15 |
| 263 | Assessing Translation Capabilities of Large Language Models Involving English and Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, our aim is to explore the multilingual capabilities of large language models by using machine translation as a task involving English and 22 Indian languages. |
VANDAN MUJADIA et. al. | arxiv-cs.CL | 2023-11-15 |
| 264 | Aligning Neural Machine Translation Models: Human Feedback in Training and Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we comprehensively explore and compare techniques for integrating quality metrics as reward models into the MT pipeline. |
Miguel Moura Ramos; Patrick Fernandes; António Farinhas; André F. T. Martins; | arxiv-cs.CL | 2023-11-15 |
| 265 | Non-autoregressive Machine Translation with Probabilistic Context-free Grammar Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, conventional NAT models suffer from limited expression power and performance degradation compared to autoregressive (AT) models due to the assumption of conditional independence among target tokens. To address these limitations, we propose a novel approach called PCFG-NAT, which leverages a specially designed Probabilistic Context-Free Grammar (PCFG) to enhance the ability of NAT models to capture complex dependencies among output tokens. |
SHANGTONG GUI et. al. | arxiv-cs.CL | 2023-11-14 |
| 266 | Extending Multilingual Machine Translation Through Imitation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We aim to extend large-scale MNMT models to a new language, allowing for translation between the newly added and all of the already supported languages in a challenging scenario: using only a parallel corpus between the new language and English. |
Wen Lai; Viktor Hangya; Alexander Fraser; | arxiv-cs.CL | 2023-11-14 |
| 267 | On-the-Fly Fusion of Large Language Models and Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose the on-the-fly ensembling of a machine translation model with an LLM, prompted on the same task and input. |
Hieu Hoang; Huda Khayrallah; Marcin Junczys-Dowmunt; | arxiv-cs.CL | 2023-11-14 |
| 268 | Investigating Multi-Pivot Ensembling with Massively Multilingual Machine Translation Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Pivoting via high-resource languages remains a strong strategy for low-resource directions, and in this paper we revisit ways of pivoting through multiple languages. |
Alireza Mohammadshahi; Jannis Vamvas; Rico Sennrich; | arxiv-cs.CL | 2023-11-13 |
| 269 | Added Toxicity Mitigation at Inference Time for Multimodal and Massively Multilingual Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Added toxicity in the context of translation refers to the fact of producing a translation output with more toxicity than there exists in the input. In this paper, we present MinTox which is a novel pipeline to identify added toxicity and mitigate this issue which works at inference time. |
Marta R. Costa-jussà; David Dale; Maha Elbayad; Bokai Yu; | arxiv-cs.CL | 2023-11-11 |
| 270 | Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To demonstrate our point, in this work, we use Hindi as the source language and construct two sets of gender-specific sentences: OTSC-Hindi and WinoMT-Hindi that we use to evaluate different Hindi-English (HI-EN) NMT systems automatically for gender bias. |
Pushpdeep Singh; | arxiv-cs.CL | 2023-11-07 |
| 271 | CBSiMT: Mitigating Hallucination in Simultaneous Machine Translation with Weighted Prefix-to-Prefix Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a Confidence-Based Simultaneous Machine Translation (CBSiMT) framework, which uses model confidence to perceive hallucination tokens and mitigates their negative impact with weighted prefix-to-prefix training. |
MENGGE LIU et. al. | arxiv-cs.CL | 2023-11-06 |
| 272 | Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To create the parallel corpora, we propose a dynamic programming based sentence alignment algorithm which leverages the cosine similarity of machine-translated sentences. |
Haiyue Song; Raj Dabre; Chenhui Chu; Atsushi Fujita; Sadao Kurohashi; | arxiv-cs.CL | 2023-11-06 |
| 273 | Findings of The WMT 2023 Shared Task on Discourse-Level Literary Translation: A Fresh Orb in The Cosmos of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We employ both automatic and human evaluations to measure the performance of the submitted systems. |
LONGYUE WANG et. al. | arxiv-cs.CL | 2023-11-06 |
| 274 | Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in Indonesia Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Neural machine translation (NMT) for low-resource local languages in Indonesia faces significant challenges, including the need for a representative benchmark and limited data availability. This work addresses these challenges by comprehensively analyzing training NMT systems for four low-resource local languages in Indonesia: Javanese, Sundanese, Minangkabau, and Balinese. |
Lucky Susanto; Ryandito Diandaru; Adila Krisnadhi; Ayu Purwarianti; Derry Wijaya; | arxiv-cs.CL | 2023-11-02 |
| 275 | Is Robustness Transferable Across Languages in Multilingual Neural Machine Translation? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the transferability of robustness across different languages in multilingual neural machine translation. |
Leiyu Pan; Deyi Xiong; | arxiv-cs.AI | 2023-10-31 |
| 276 | Towards A Deep Understanding of Multilingual End-to-End Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we employ Singular Value Canonical Correlation Analysis (SVCCA) to analyze representations learnt in a multilingual end-to-end speech translation model trained over 22 languages. |
Haoran Sun; Xiaohu Zhao; Yikun Lei; Shaolin Zhu; Deyi Xiong; | arxiv-cs.CL | 2023-10-31 |
| 277 | Cultural Adaptation of Recipes Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a new task involving the translation and cultural adaptation of recipes between Chinese and English-speaking cuisines. |
YONG CAO et. al. | arxiv-cs.CL | 2023-10-26 |
| 278 | Incorporating Probing Signals Into Multimodal Machine Translation Via Visual Question-Answering Pairs Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents an in-depth study of multimodal machine translation (MMT), examining the prevailing understanding that MMT systems exhibit decreased sensitivity to visual information when text inputs are complete. |
YUXIN ZUO et. al. | arxiv-cs.CL | 2023-10-26 |
| 279 | DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Towards the goal of multilingual disfluency correction, we present a high-quality human-annotated DC corpus covering four important Indo-European languages: English, Hindi, German and French. |
Vineet Bhat; Preethi Jyothi; Pushpak Bhattacharyya; | arxiv-cs.CL | 2023-10-25 |
| 280 | CUNI Submission to MRL 2023 Shared Task on Multi-lingual Multi-task Information Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To keep the inferred tags on the correct positions in the original language, we propose a method based on scoring the candidate positions using a label-sensitive translation model. |
Jindřich Helcl; Jindřich Libovický; | arxiv-cs.CL | 2023-10-25 |
| 281 | ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present ComSL, a speech-language model built atop a composite architecture of public pre-trained speech-only and language-only models and optimized data-efficiently for spoken language tasks. |
CHENYANG LE et. al. | nips | 2023-10-24 |
| 282 | Machine Translation for Nko: Tools, Corpora and Baseline Results Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Currently, there is no usable machine translation system for Nko, a language spoken by tens of millions of people across multiple West African countries, which holds significant cultural and educational value. To address this issue, we present a set of tools, resources, and baseline results aimed towards the development of usable machine translation systems for Nko and other languages that do not currently have sufficiently large parallel text corpora available. |
MOUSSA KOULAKO BALA DOUMBOUYA et. al. | arxiv-cs.CL | 2023-10-24 |
| 283 | Data Augmentation Techniques for Machine Translation of Code-Switched Texts: A Comparative Study Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we compare three popular approaches: lexical replacements, linguistic theories, and back-translation (BT), in the context of Egyptian Arabic-English CSW. |
Injy Hamed; Nizar Habash; Ngoc Thang Vu; | arxiv-cs.CL | 2023-10-23 |
| 284 | PartialFormer: Modeling Part Instead of Whole for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we emphasize the importance of hidden dimensions in designing lightweight FFNs, a factor often overlooked in previous architectures. |
TONG ZHENG et. al. | arxiv-cs.CL | 2023-10-23 |
| 285 | Domain Terminology Integration Into Machine Translation: Leveraging Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper discusses the methods that we used for our submissions to the WMT 2023 Terminology Shared Task for German-to-English (DE-EN), English-to-Czech (EN-CS), and Chinese-to-English (ZH-EN) language pairs. |
D. Kelleher; | arxiv-cs.CL | 2023-10-22 |
| 286 | Boosting Unsupervised Machine Translation with Pseudo-Parallel Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a training strategy that relies on pseudo-parallel sentence pairs mined from monolingual corpora in addition to synthetic sentence pairs back-translated from monolingual corpora. |
Ivana Kvapilíková; Ondřej Bojar; | arxiv-cs.CL | 2023-10-22 |
| 287 | Evaluating and Optimizing The Effectiveness of Neural Machine Translation in Supporting Code Retrieval Models: A Study on The CAT Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we analyze the performance of NMT in natural language-to-code translation in the newly curated CAT benchmark[31] that includes the optimized versions of three Java datasets TLCodeSum, CodeSearchNet, Funcom, and a Python dataset PCSD. |
Hung Phan; Ali Jannesari; | cikm | 2023-10-21 |
| 288 | Code-Switching with Word Senses for Pretraining in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Word Sense Pretraining for Neural Machine Translation (WSP-NMT) – an end-to-end approach for pretraining multilingual NMT models leveraging word sense-specific information from Knowledge Bases. |
Vivek Iyer; Edoardo Barba; Alexandra Birch; Jeff Z. Pan; Roberto Navigli; | arxiv-cs.CL | 2023-10-21 |
| 289 | Translation Performance from The User’s Perspective of Large Language Models and Neural Machine Translation Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The rapid global expansion of ChatGPT, which plays a crucial role in interactive knowledge sharing and translation, underscores the importance of comparative performance … |
Jungha Son; Boyoung Kim; | Inf. | 2023-10-19 |
| 290 | A Tale of Pronouns: Interpretability Informs Gender Bias Mitigation for Fairer Instruction-Tuned Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In MT, this might lead to misgendered translations, resulting, among other harms, in the perpetuation of stereotypes and prejudices. In this work, we address this gap by investigating whether and to what extent such models exhibit gender bias in machine translation and how we can mitigate it. |
Giuseppe Attanasio; Flor Miriam Plaza-del-Arco; Debora Nozza; Anne Lauscher; | arxiv-cs.CL | 2023-10-18 |
| 291 | Direct Neural Machine Translation with Task-level Mixture of Experts Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we examine Task-level MoE’s applicability in direct NMT and propose a series of high-performing training and evaluation configurations, through which Task-level MoE-based direct NMT systems outperform bilingual and pivot-based models for a large number of low and high-resource direct pairs, and translation directions. |
Isidora Chara Tourni; Subhajit Naskar; | arxiv-cs.CL | 2023-10-18 |
| 292 | Knn-seq: Efficient, Extensible KNN-MT Framework Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present an efficient and extensible kNN-MT framework, knn-seq, for researchers and developers that is carefully designed to run efficiently, even with a billion-scale large datastore. |
HIROYUKI DEGUCHI et. al. | arxiv-cs.CL | 2023-10-18 |
| 293 | Long-form Simultaneous Speech Translation: Thesis Proposal Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This thesis proposal addresses end-to-end simultaneous speech translation, particularly in the long-form setting, i.e., without pre-segmentation. We present a survey of the latest advancements in E2E SST, assess the primary obstacles in SST and its relevance to long-form scenarios, and suggest approaches to tackle these challenges. |
Peter Polák; | arxiv-cs.CL | 2023-10-17 |
| 294 | An Empirical Study of Translation Hypothesis Ensembling with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we investigate how hypothesis ensembling can improve the quality of the generated text for the specific problem of LLM-based machine translation. |
António Farinhas; José G. C. de Souza; André F. T. Martins; | arxiv-cs.CL | 2023-10-17 |
| 295 | Exploring Automatic Evaluation Methods Based on A Decoder-based LLM for Text Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper compares various methods, including tuning with encoder-based models and large language models under equal conditions, on two different tasks, machine translation evaluation and semantic textual similarity, in two languages, Japanese and English. |
Tomohito Kasahara; Daisuke Kawahara; | arxiv-cs.CL | 2023-10-17 |
| 296 | UvA-MT’s Participation in The WMT23 General Translation Shared Task Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes the UvA-MT’s submission to the WMT 2023 shared task on general machine translation. |
Di Wu; Shaomu Tan; David Stap; Ali Araabi; Christof Monz; | arxiv-cs.CL | 2023-10-15 |
| 297 | Improving Access to Justice for The Indian Population: A Benchmark for Evaluating Translation of Legal Text to Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we construct the first high-quality legal parallel corpus containing aligned text units in English and nine Indian languages, that includes several low-resource languages. |
Sayan Mahapatra; Debtanu Datta; Shubham Soni; Adrijit Goswami; Saptarshi Ghosh; | arxiv-cs.CL | 2023-10-15 |
| 298 | Human-in-the-loop Machine Translation with Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this study, we propose a human-in-the-loop pipeline that guides LLMs to produce customized outputs with revision instructions. |
Xinyi Yang; Runzhe Zhan; Derek F. Wong; Junchao Wu; Lidia S. Chao; | arxiv-cs.CL | 2023-10-13 |
| 299 | Political Claim Identification and Categorization in A Multilingual Setting: First Experiments Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper explores different strategies for the cross-lingual projection of political claims analysis. |
Urs Zaberer; Sebastian Padó; Gabriella Lapesa; | arxiv-cs.CL | 2023-10-13 |
| 300 | XDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To address the issue, we introduce xDial-Eval, built on top of open-source English dialogue evaluation datasets. |
CHEN ZHANG et. al. | arxiv-cs.CL | 2023-10-13 |
| 301 | Enhancing Expressivity Transfer in Textless Speech-to-speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Expressivity plays a vital role in conveying emotions, nuances, and cultural subtleties, thereby enhancing communication across diverse languages. To address this issue this study presents a novel method that operates at the discrete speech unit level and leverages multilingual emotion embeddings to capture language-agnostic information. |
Jarod Duret; Benjamin O’Brien; Yannick Estève; Titouan Parcollet; | arxiv-cs.SD | 2023-10-11 |
| 302 | Larth: Dataset and Machine Translation for Etruscan Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To the best of our knowledge, there are no publicly available Etruscan corpora for natural language processing. Therefore, we propose a dataset for machine translation from Etruscan to English, which contains 2891 translated examples from existing academic sources. |
Gianluca Vico; Gerasimos Spanakis; | arxiv-cs.CL | 2023-10-09 |
| 303 | Terminology-Aware Translation with Constrained Decoding and Large Language Model Prompting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Alternatively, we leverage a large language model to refine a hypothesis by providing it with terminology constraints. |
Nikolay Bogoychev; Pinzhen Chen; | arxiv-cs.CL | 2023-10-09 |
| 304 | All Translation Tools Are Not Equal: Investigating The Quality of Language Translation for Forced Migration Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As the volume and complexity of forced movement continues to grow, there is an urgent need to use new data sources to better understand emerging crises. Organic sources, like … |
AMEETA AGRAWAL et. al. | 2023 IEEE 10th International Conference on Data Science and … | 2023-10-09 |
| 305 | Synslator: An Interactive Machine Translation Tool with Online Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces Synslator, a user-friendly computer-aided translation (CAT) tool that not only supports IMT, but is adept at online learning with real-time translation memories. |
JIAYI WANG et. al. | arxiv-cs.CL | 2023-10-08 |
| 306 | CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop multilingual modeling approaches for code translation and demonstrate their great potential in improving the translation quality of both low-resource and high-resource language pairs and boosting the training efficiency. |
Weixiang Yan; Yuchen Tian; Yunzhe Li; Qian Chen; Wen Wang; | arxiv-cs.AI | 2023-10-07 |
| 307 | Evaluation of Cross-Lingual Bug Localization: Two Industrial Cases Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This study reports the results of applying the cross-lingual bug localization approach proposed by Xia et al. to industrial software projects. |
Shinpei Hayashi; Takashi Kobayashi; Tadahisa Kato; | arxiv-cs.SE | 2023-10-03 |
| 308 | Tuning Large Language Model for End-to-end Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper introduces LST, a Large multimodal model designed to excel at the E2E-ST task. |
HAO ZHANG et. al. | arxiv-cs.CL | 2023-10-03 |
| 309 | Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To understand when and why the navigation capabilities of language IDs are weakened, we compare two extreme decoder input cases in the ZST directions: Off-Target (OFF) and On-Target (ON) cases. |
CHANGTONG ZAN et. al. | arxiv-cs.CL | 2023-09-28 |
| 310 | MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and Recognition IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Nonetheless, visual speech is not as distinguishable as audio speech, making it difficult to develop a mapping from source speech phonemes to the target language text. To address this issue, we propose MixSpeech, a cross-modality self-learning framework that utilizes audio speech to regularize the training of visual speech tasks. |
XIZE CHENG et. al. | iccv | 2023-09-27 |
| 311 | CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, these are not directly applicable to MMT since they do not provide aligned multimodal multilingual features for generative tasks. To alleviate this issue, instead of designing complex modules for MMT, we propose CLIPTrans, which simply adapts the independently pre-trained multimodal M-CLIP and the multilingual mBART. |
DEVAANSH GUPTA et. al. | iccv | 2023-09-27 |
| 312 | Direct Models for Simultaneous Translation and Automatic Subtitling: FBK@IWSLT2023 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper describes the FBK’s participation in the Simultaneous Translation and Automatic Subtitling tracks of the IWSLT 2023 Evaluation Campaign. |
Sara Papi; Marco Gaido; Matteo Negri; | arxiv-cs.CL | 2023-09-27 |
| 313 | Segmentation-Free Streaming Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper proposes a Segmentation-Free framework that enables the model to translate an unsegmented source stream by delaying the segmentation decision until the translation has been generated. |
Javier Iranzo-Sánchez; Jorge Iranzo-Sánchez; Adrià Giménez; Jorge Civera; Alfons Juan; | arxiv-cs.CL | 2023-09-26 |
| 314 | Hindi to English: Transformer-Based Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we have developed a Neural Machine Translation (NMT) system by training the Transformer model to translate texts from Indian Language Hindi to English. |
Kavit Gangar; Hardik Ruparel; Shreyas Lele; | arxiv-cs.CL | 2023-09-22 |
| 315 | Audience-specific Explanations for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we explore techniques to extract example explanations from a parallel corpus. |
Renhan Lou; Jan Niehues; | arxiv-cs.CL | 2023-09-22 |
| 316 | Domain Adaptation for Arabic Machine Translation: The Case of Financial Texts Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: To this end, we developed carefully a parallel corpus for Arabic-English (AR- EN) translation in the financial domain for benchmarking different domain adaptation methods. |
Emad A. Alghamdi; Jezia Zakraoui; Fares A. Abanmy; | arxiv-cs.CL | 2023-09-22 |
| 317 | OSN-MDAD: Machine Translation Dataset for Arabic Multi-Dialectal Conversations on Online Social Media Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While few attempts have been made to build translation datasets for dialectal Arabic, they are domain dependent and are not OSN cultural-language friendly. In this work, we attempt to alleviate these limitations by proposing an online social network-based multidialect Arabic dataset that is crafted by contextually translating English tweets into four Arabic dialects: Gulf, Yemeni, Iraqi, and Levantine. |
Fatimah Alzamzami; Abdulmotaleb El Saddik; | arxiv-cs.CL | 2023-09-21 |
| 318 | SpeechAlign: A Framework for Speech Translation Alignment Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Speech-to-Speech and Speech-to-Text translation are currently dynamic areas of research. In our commitment to advance these fields, we present SpeechAlign, a framework designed to evaluate the underexplored field of source-target alignment in speech models. |
Belen Alastruey; Aleix Sant; Gerard I. Gállego; David Dale; Marta R. Costa-jussà; | arxiv-cs.CL | 2023-09-20 |
| 319 | SignBank+: Preparing A Multilingual Sign Language Dataset for Machine Translation Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce SignBank+, a clean version of the SignBank dataset, optimized for machine translation between spoken language text and SignWriting, a phonetic sign language writing system. |
Amit Moryossef; Zifan Jiang; | arxiv-cs.CL | 2023-09-20 |
| 320 | NSOAMT — New Search Only Approach to Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The idea is to develop a solution that, by indexing an incremental set of words that combine a certain semantic meaning, makes it possible to create a process of correspondence between their native language record and the language of translation. |
João Luís; Diogo Cardoso; José Marques; Luís Campos; | arxiv-cs.CL | 2023-09-19 |
| 321 | LoGenText-Plus: Improving Neural Machine Translation-based Logging Texts Generation with Syntactic Templates Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Developers insert logging statements in the source code to collect important runtime information about software systems. The textual descriptions in logging statements (i.e., … |
Zishuo Ding; Yiming Tang; Xiaoyu Cheng; Heng Li; Weiyi Shang; | ACM Transactions on Software Engineering and Methodology | 2023-09-18 |
| 322 | Controllability for English-Ukrainian Machine Translation By Using Style Transfer Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: While straightforward machine translation got significant improvements in the last 10 years with the arrival of encoder-decoder neural networks and transformers architecture, … |
DANIIL MAKSYMENKO et. al. | 2023 18th Conference on Computer Science and Intelligence … | 2023-09-17 |
| 323 | Neural Machine Translation Models Can Learn to Be Few-shot Learners Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we show that a much smaller model can be trained to perform ICL by fine-tuning towards a specialized training objective, exemplified on the task of domain adaptation for neural machine translation. |
Raphael Reinauer; Patrick Simianer; Kaden Uhlig; Johannes E. M. Mosig; Joern Wuebker; | arxiv-cs.CL | 2023-09-15 |
| 324 | Mitigating Hallucinations and Off-target Machine Translation with Source-Contrastive and Language-Contrastive Decoding IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Hallucinations and off-target translation remain unsolved problems in MT, especially for low-resource languages and massively multilingual models. In this paper, we introduce two related methods to mitigate these failure cases with a modified decoding objective, without either requiring retraining or external models. |
Rico Sennrich; Jannis Vamvas; Alireza Mohammadshahi; | arxiv-cs.CL | 2023-09-13 |
| 325 | Dual-view Curricular Optimal Transport for Cross-lingual Cross-modal Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Improperly assuming the pseudo-parallel data are correctly correlated will make the networks overfit to the noisy correspondence. Therefore, we propose Dual-view Curricular Optimal Transport (DCOT) to learn with noisy correspondence in CCR. |
YABING WANG et. al. | arxiv-cs.CV | 2023-09-11 |
| 326 | The Effect of Alignment Objectives on Code-Switching Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we are proposing a way of training a single machine translation model that is able to translate monolingual sentences from one language to another, along with translating code-switched sentences to either language. |
Mohamed Anwar; | arxiv-cs.CL | 2023-09-10 |
| 327 | Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a novel approach Epi-Curriculum to address low-resource domain adaptation (DA), which contains a new episodic training framework along with denoised curriculum learning. |
Keyu Chen; Di Zhuang; Mingchen Li; J. Morris Chang; | arxiv-cs.LG | 2023-09-05 |
| 328 | Advancing Text-to-GLOSS Neural Translation Using A Novel Hyper-parameter Optimization Technique Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate the use of transformers for Neural Machine Translation of text-to-GLOSS for Deaf and Hard-of-Hearing communication. |
Younes Ouargani; Noussaima El Khattabi; | arxiv-cs.CL | 2023-09-05 |
| 329 | Exploration of Low-resource Language-oriented Machine Translation System of Genetic Algorithm-optimized Hyper-task Network Under Cloud Platform Technology Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xiao Liu; Junlong Chen; Deyu Qi; Tong Zhang; | J. Supercomput. | 2023-09-04 |
| 330 | Neural Machine Translation Systems for English to Khasi: A Case Study of An Austroasiatic Language Related Papers Related Patents Related Grants Related Venues Related Experts View |
A. V. Hujon; Thoudam Doren Singh; Khwairakpam Amitab; | Expert Syst. Appl. | 2023-09-01 |
| 331 | Impact of Visual Context on Noisy Multimodal NMT: An Empirical Study for English to Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The study investigates the effectiveness of utilizing multimodal information in Neural Machine Translation (NMT). |
Baban Gain; Dibyanayan Bandyopadhyay; Samrat Mukherjee; Chandranath Adak; Asif Ekbal; | arxiv-cs.CL | 2023-08-30 |
| 332 | Training and Meta-Evaluating Machine Translation Evaluation Metrics at The Paragraph Level Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As research on machine translation moves to translating text beyond the sentence level, it remains unclear how effective automatic evaluation metrics are at scoring longer … |
Daniel Deutsch; Juraj Juraska; Mara Finkelstein; Markus Freitag; | arxiv-cs.CL | 2023-08-25 |
| 333 | Improving Translation Faithfulness of Large Language Models Via Augmenting Instructions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Large Language Models (LLMs) present strong general capabilities, and a current compelling challenge is stimulating their specialized capabilities, such as machine translation, through low-cost instruction tuning. |
YIJIE CHEN et. al. | arxiv-cs.CL | 2023-08-24 |
| 334 | SONAR: Sentence-Level Multimodal and Language-Agnostic Representations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce SONAR, a new multilingual and multimodal fixed-size sentence embedding space. |
Paul-Ambroise Duquenne; Holger Schwenk; Benoît Sagot; | arxiv-cs.CL | 2023-08-22 |
| 335 | SeamlessM4T: Massively Multilingual & Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: More specifically, conventional speech-to-speech translation systems rely on cascaded systems that perform translation progressively, putting high-performing unified systems out of reach. To address these gaps, we introduce SeamlessM4T, a single model that supports speech-to-speech translation, speech-to-text translation, text-to-speech translation, text-to-text translation, and automatic speech recognition for up to 100 languages. |
SEAMLESS COMMUNICATION et. al. | arxiv-cs.CL | 2023-08-22 |
| 336 | An Effective Method Using Phrase Mechanism in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we report an effective method using a phrase mechanism, PhraseTransformer, to improve the strong baseline model Transformer in constructing a Neural Machine Translation (NMT) system for parallel corpora Vietnamese-Chinese. |
Phuong Minh Nguyen; Le Minh Nguyen; | arxiv-cs.CL | 2023-08-21 |
| 337 | Towards Multi-Lingual Audio Question Answering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Audio Question Answering (AQA) is a multi-modal translation task where a system analyzes an audio signal and a natu-ral language question to generate a desirable natural language … |
Swarup Ranjan Behera; Pailla Balakrishna Reddy; A. Tripathi; Megavath Bharadwaj Rathod; Tejesh Karavadi; | Interspeech | 2023-08-20 |
| 338 | Factuality Detection Using Machine Translation — A Use Case for German Clinical Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In the context of factuality detection, this work presents a simple solution using machine translation to translate English data to German to train a transformer-based factuality detection model. |
Mohammed Bin Sumait; Aleksandra Gabryszak; Leonhard Hennig; Roland Roller; | arxiv-cs.CL | 2023-08-17 |
| 339 | Fast Training of NMT Model with Data Sorting Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: One potential area for improvement is to address the computation of empty tokens that the Transformer computes only to discard them later, leading to an unnecessary computational burden. To tackle this, we propose an algorithm that sorts translation sentence pairs based on their length before batching, minimizing the waste of computing power. |
Daniela N. Rim; Kimera Richard; Heeyoul Choi; | arxiv-cs.CL | 2023-08-16 |
| 340 | VBD-MT Chinese-Vietnamese Translation Systems for VLSP 2022 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present our systems participated in the VLSP 2022 machine translation shared task. |
Hai Long Trieu; Song Kiet Bui; Tan Minh Tran; Van Khanh Tran; Hai An Nguyen; | arxiv-cs.CL | 2023-08-15 |
| 341 | Extrapolating Large Language Models to Non-English By Aligning Languages IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we empower pre-trained LLMs on non-English languages by building semantic alignment across languages. |
WENHAO ZHU et. al. | arxiv-cs.CL | 2023-08-09 |
| 342 | Character-level NMT and Language Similarity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We evaluate the models using automatic MT metrics and show that translation between similar languages benefits from character-level input segmentation, while for less related languages, character-level vanilla Transformer-base often lags behind subword-level segmentation. |
Josef Jon; Ondřej Bojar; | arxiv-cs.CL | 2023-08-08 |
| 343 | Negative Lexical Constraints in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We compared various methods based on modifying either the decoding process or the training data. |
Josef Jon; Dušan Variš; Michal Novák; João Paulo Aires; Ondřej Bojar; | arxiv-cs.CL | 2023-08-07 |
| 344 | Show Me The World in My Language: Establishing The First Baseline for Scene-Text to Scene-Text Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the task of “visually” translating scene text from a source language (e.g., Hindi) to a target language (e.g., English). |
Shreyas Vaidya; Arvind Kumar Sharma; Prajwal Gatti; Anand Mishra; | arxiv-cs.CV | 2023-08-06 |
| 345 | Do Multilingual Language Models Think Better in English? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we introduce a new approach called self-translate, which overcomes the need of an external translation system by leveraging the few-shot translation capabilities of multilingual language models. |
Julen Etxaniz; Gorka Azkune; Aitor Soroa; Oier Lopez de Lacalle; Mikel Artetxe; | arxiv-cs.CL | 2023-08-02 |
| 346 | Structural Transfer Learning in NL-to-Bash Semantic Parsers Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a methodology for obtaining a quantitative understanding of structural overlap between machine translation tasks. |
Kyle Duffy; Satwik Bhattamishra; Phil Blunsom; | arxiv-cs.CL | 2023-07-31 |
| 347 | MTUncertainty: Assessing The Need for Post-editing of Machine Translation Outputs By Fine-tuning OpenAI LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We take OpenAI models as the best state-of-the-art technology and approach TQE as a binary classification task. |
Serge Gladkoff; Lifeng Han; Gleb Erofeev; Irina Sorokina; Goran Nenadic; | arxiv-cs.CL | 2023-07-31 |
| 348 | Predicting Perfect Quality Segments in MT Output with Fine-Tuned OpenAI LLM: Is It Possible to Capture Editing Distance Patterns from Historical Data? Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Translation Quality Estimation (TQE) is an essential step before deploying the output translation into usage. TQE is also critical in assessing machine translation (MT) and human … |
Serge Gladkoff; G. Erofeev; Lifeng Han; G. Nenadic; | ArXiv | 2023-07-31 |
| 349 | Toward Quantum Machine Translation of Syntactically Distinct Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The present study aims to explore the feasibility of language translation using quantum natural language processing algorithms on noisy intermediate-scale quantum (NISQ) devices. |
Mina Abbaszade; Mariam Zomorodi; Vahid Salari; Philip Kurian; | arxiv-cs.CL | 2023-07-31 |
| 350 | Multilingual Lexical Simplification Via Paraphrase Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a novel multilingual LS method via paraphrase generation, as paraphrases provide diversity in word selection while preserving the sentence’s meaning. |
KANG LIU et. al. | arxiv-cs.CL | 2023-07-27 |
| 351 | XDLM: Cross-lingual Diffusion Language Model for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Additionally, while pretraining with diffusion models has been studied within a single language, the potential of cross-lingual pretraining remains understudied. To address these gaps, we propose XDLM, a novel Cross-lingual diffusion model for machine translation, consisting of pretraining and fine-tuning stages. |
Linyao Chen; Aosong Feng; Boming Yang; Zihui Li; | arxiv-cs.CL | 2023-07-25 |
| 352 | Lost In Translation: Generating Adversarial Examples Robust to Round-Trip Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a comprehensive study on the robustness of current text adversarial attacks to round-trip translation. |
Neel Bhandari; Pin-Yu Chen; | arxiv-cs.CL | 2023-07-24 |
| 353 | Incorporating Human Translator Style Into English-Turkish Literary Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we focus on English-Turkish literary translation and develop machine translation models that take into account the stylistic features of translators. |
ZEYNEP YIRMIBEŞOĞLU et. al. | arxiv-cs.CL | 2023-07-21 |
| 354 | Construction of Mizo: English Parallel Corpus for Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Parallel corpus is a key component of statistical and Neural Machine Translation (NMT). While most research focuses on machine translation, corpus creation studies are limited for … |
Thangkhanhau Haulai; J. Hussain; | ACM Transactions on Asian and Low-Resource Language … | 2023-07-21 |
| 355 | Improving End-to-End Speech Translation By Imitation-Based Knowledge Distillation with Synthetic Transcripts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present an imitation learning approach where a teacher NMT system corrects the errors of an AST student without relying on manual transcripts. |
Rebekka Hubert; Artem Sokolov; Stefan Riezler; | arxiv-cs.CL | 2023-07-17 |
| 356 | Investigating Unsupervised Neural Machine Translation for Low-resource Language Pair English-Mizo Via Lexically Enhanced Pre-trained Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: The vast majority of languages in the world at present are considered to be low-resource languages. Since the availability of large parallel data is crucial for the success of … |
C. Lalrempuii; B. Soni; | ACM Transactions on Asian and Low-Resource Language … | 2023-07-13 |
| 357 | Data Augmentation for Machine Translation Via Dependency Subtree Swapping Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a generic framework for data augmentation via dependency subtree swapping that is applicable to machine translation. |
Attila Nagy; Dorina Petra Lakatos; Botond Barta; Patrick Nanys; Judit Ács; | arxiv-cs.CL | 2023-07-13 |
| 358 | The NPU-MSXF Speech-to-Speech Translation System for IWSLT 2023 Speech-to-Speech Translation Task Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes the NPU-MSXF system for the IWSLT 2023 speech-to-speech translation (S2ST) task which aims to translate from English speech of multi-source to Chinese speech. |
KUN SONG et. al. | arxiv-cs.SD | 2023-07-10 |
| 359 | TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a parallel tense test set, containing French-English 552 utterances. |
Yiming Ai; Zhiwei He; Kai Yu; Rui Wang; | acl | 2023-07-08 |
| 360 | Using Neural Machine Translation for Generating Diverse Challenging Exercises for Language Learner Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose a novel approach to automatically generate distractors for cloze exercises for English language learners, using round-trip neural machine translation. |
Frank Palma Gomez; Subhadarshi Panda; Michael Flor; Alla Rozovskaya; | acl | 2023-07-08 |
| 361 | Understanding and Bridging The Modality Gap for Speech Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We find that the modality gap is relatively small during training except for some difficult cases, but keeps increasing during inference due to the cascading effect. To address these problems, we propose the Cross-modal Regularization with Scheduled Sampling (Cress) method. |
Qingkai Fang; Yang Feng; | acl | 2023-07-08 |
| 362 | A Survey on Zero Pronoun Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This phenomenon has been studied extensively in machine translation (MT), as it poses a significant challenge for MT systems due to the difficulty in determining the correct antecedent for the pronoun. This survey paper highlights the major works that have been undertaken in zero pronoun translation (ZPT) after the neural revolution so that researchers can recognize the current state and future directions of this field. |
LONGYUE WANG et. al. | acl | 2023-07-08 |
| 363 | Simple and Effective Unsupervised Speech Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The amount of labeled data to train models for speech tasks is limited for most languages, however, the data scarcity is exacerbated for speech translation which requires labeled data covering two different languages. To address this issue, we study a simple and effective approach to build speech translation systems without labeled data by leveraging recent advances in unsupervised speech recognition, machine translation and speech synthesis, either in a pipeline approach, or to generate pseudo-labels for training end-to-end speech translation models. |
CHANGHAN WANG et. al. | acl | 2023-07-08 |
| 364 | Exploring Better Text Image Translation with Multimodal Codebook Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we first annotate a Chinese-English TIT dataset named OCRMT30K, providing convenience for subsequent studies. |
ZHIBIN LAN et. al. | acl | 2023-07-08 |
| 365 | MCLIP: Multilingual CLIP Via Cross-lingual Transfer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce mCLIP, a retrieval-efficient dual-stream multilingual VLP model, trained by aligning the CLIP model and a Multilingual Text Encoder (MTE) through a novel Triangle Cross-modal Knowledge Distillation (TriKD) method. |
GUANHUA CHEN et. al. | acl | 2023-07-08 |
| 366 | INK: Injecting KNN Knowledge in Nearest Neighbor Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose an effective training framework INK to directly smooth the representation space via adjusting representations of kNN neighbors with a small number of new parameters. |
Wenhao Zhu; Jingjing Xu; Shujian Huang; Lingpeng Kong; Jiajun Chen; | acl | 2023-07-08 |
| 367 | PEIT: Bridging The Modality Gap with Pre-trained Models for End-to-End Image Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose PEIT, an end-to-end image translation framework that bridges the modality gap with pre-trained models. |
Shaolin Zhu; Shangjie Li; Yikun Lei; Deyi Xiong; | acl | 2023-07-08 |
| 368 | Learning Optimal Policy for Simultaneous Machine Translation Via Binary Search IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a new method for constructing the optimal policy online via binary search. |
Shoutao Guo; Shaolei Zhang; Yang Feng; | acl | 2023-07-08 |
| 369 | Multilingual Event Extraction from Historical Newspaper Adverts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a new multilingual dataset in English, French, and Dutch composed of newspaper ads from the early modern colonial period reporting on enslaved people who liberated themselves from enslavement. |
Nadav Borenstein; Nat�lia da Silva Perez; Isabelle Augenstein; | acl | 2023-07-08 |
| 370 | Easy Guided Decoding in Providing Suggestions for Interactive Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we utilize the parameterized objective function of neural machine translation (NMT) and propose a novel constrained decoding algorithm, namely Prefix-Suffix Guided Decoding (PSGD), to deal with the TS problem without additional training. |
Ke Wang; Xin Ge; Jiayi Wang; Yuqi Zhang; Yu Zhao; | acl | 2023-07-08 |
| 371 | Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Firstly, the current objective of KD spreads its focus to whole distributions to learn the knowledge, yet lacks special treatment on the most crucial top-1 information. Secondly, the knowledge is largely covered by the golden information due to the fact that most top-1 predictions of teachers overlap with ground-truth tokens, which further restricts the potential of KD. To address these issues, we propose a new method named Top-1 Information Enhanced Knowledge Distillation (TIE-KD). |
SONGMING ZHANG et. al. | acl | 2023-07-08 |
| 372 | Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To eliminate the rule-based nature of data creation, we instead propose using machine translation models to create gender-biased text from real gender-fair text via round-trip translation. |
Chantal Amrhein; Florian Schottmann; Rico Sennrich; Samuel L�ubli; | acl | 2023-07-08 |
| 373 | RAMP: Retrieval and Attribute-Marking Enhanced Prompting for Attribute-Controlled Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While ACT has garnered attention in recent years due to its usefulness in real-world applications, progress in the task is currently limited by dataset availability, since most prior approaches rely on supervised methods. To address this limitation, we propose Retrieval and Attribute-Marking enhanced Prompting (RAMP), which leverages large multilingual language models to perform ACT in few-shot and zero-shot settings. |
GABRIELE SARTI et. al. | acl | 2023-07-08 |
| 374 | Back Translation for Speech-to-text Translation Without Transcripts IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we aim to utilize large amounts of target-side monolingual data to enhance ST without transcripts. |
Qingkai Fang; Yang Feng; | acl | 2023-07-08 |
| 375 | What About �em�? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Wrong pronoun translations can discriminate against marginalized groups, e. g. , non-binary individuals (Dev et al. , 2021). In this �reality check�, we study how three commercial MT systems translate 3rd-person pronouns. |
Anne Lauscher; Debora Nozza; Ehm Miltersen; Archie Crowley; Dirk Hovy; | acl | 2023-07-08 |
| 376 | CMOT: Cross-modal Mixup Via Optimal Transport for Speech Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose Cross-modal Mixup via Optimal Transport (CMOT) to overcome the modality gap. |
Yan Zhou; Qingkai Fang; Yang Feng; | acl | 2023-07-08 |
| 377 | Translation-Enhanced Multilingual Text-to-Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We provide two key contributions. 1) Relying on a multilingual multi-modal encoder, we provide a systematic empirical study of standard methods used in cross-lingual NLP when applied to mTTI: Translate Train, Translate Test, and Zero-Shot Transfer. 2) We propose Ensemble Adapter (EnsAd), a novel parameter-efficient approach that learns to weigh and consolidate the multilingual text knowledge within the mTTI framework, mitigating the language gap and thus improving mTTI performance. |
Yaoyiran Li; Ching-Yun Chang; Stephen Rawls; Ivan Vulic; Anna Korhonen; | acl | 2023-07-08 |
| 378 | Do GPTs Produce Less Literal Translations? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, there has been relatively little investigation on how such translations differ qualitatively from the translations generated by standard Neural Machine Translation (NMT) models. In this work, we investigate these differences in terms of the literalness of translations produced by the two systems. |
Vikas Raunak; Arul Menezes; Matt Post; Hany Hassan; | acl | 2023-07-08 |
| 379 | Rethinking Multimodal Entity and Relation Extraction from A Translation Point of View Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We revisit the multimodal entity and relation extraction from a translation point of view. |
Changmeng Zheng; Junhao Feng; Yi Cai; Xiaoyong Wei; Qing Li; | acl | 2023-07-08 |
| 380 | Scene Graph As Pivoting: Inference-time Image-free Unsupervised Multimodal Machine Translation with Visual Scene Hallucination IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we investigate a more realistic unsupervised multimodal machine translation (UMMT) setup, inference-time image-free UMMT, where the model is trained with source-text image pairs, and tested with only source-text inputs. |
Hao Fei; Qian Liu; Meishan Zhang; Min Zhang; Tat-Seng Chua; | acl | 2023-07-08 |
| 381 | A Simple Concatenation Can Effectively Improve Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by the works of video Transformer, we propose a simple unified cross-modal ST method, which concatenates speech and text as the input, and builds a teacher that can utilize both cross-modal information simultaneously. |
Linlin Zhang; Kai Fan; Boxing Chen; Luo Si; | acl | 2023-07-08 |
| 382 | Searching for Needles in A Haystack: On The Role of Incidental Bilingualism in PaLM�s Translation Capability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a mixed-method approach to measure and understand incidental bilingualism at scale. |
Eleftheria Briakou; Colin Cherry; George Foster; | acl | 2023-07-08 |
| 383 | Cross2StrA: Unpaired Cross-lingual Image Captioning with Cross-lingual Cross-modal Structure-pivoted Alignment IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Unpaired cross-lingual image captioning has long suffered from irrelevancy and disfluency issues, due to the inconsistencies of the semantic scene and syntax attributes during transfer. In this work, we propose to address the above problems by incorporating the scene graph (SG) structures and the syntactic constituency (SC) trees. |
Shengqiong Wu; Hao Fei; Wei Ji; Tat-Seng Chua; | acl | 2023-07-08 |
| 384 | Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a simple yet efficient approach to adapt VLP to unseen languages using MPLM. |
Yasmine Karoui; R�mi Lebret; Negar Foroutan Eghlidi; Karl Aberer; | acl | 2023-07-08 |
| 385 | XPQA: Cross-Lingual Product Question Answering in 12 Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: While existing work on PQA focuses mainly on English, in practice there is need to support multiple customer languages while leveraging product information available in English. To study this practical industrial task, we present xPQA, a large-scale annotated cross-lingual PQA dataset in 12 languages, and report results in (1) candidate ranking, to select the best English candidate containing the information to answer a non-English question; and (2) answer generation, to generate a natural-sounding non-English answer based on the selected English candidate. |
Xiaoyu Shen; Akari Asai; Bill Byrne; Adria De Gispert; | acl | 2023-07-08 |
| 386 | Subset Retrieval Nearest Neighbor Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose �Subset kNN-MT�, which improves the decoding speed of kNN-MT by two methods: (1) retrieving neighbor target tokens from a subset that is the set of neighbor sentences of the input sentence, not from all sentences, and (2) efficient distance computation technique that is suitable for subset neighbor search using a look-up table. |
HIROYUKI DEGUCHI et. al. | acl | 2023-07-08 |
| 387 | Tackling Ambiguity with Images: Improved Multimodal Machine Translation and Contrastive Evaluation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a new MMT approach based on a strong text-only MT model, which uses neural adapters, a novel guided self-attention mechanism and which is jointly trained on both visually-conditioned masking and MMT. |
Matthieu Futeral; Cordelia Schmid; Ivan Laptev; Beno�t Sagot; Rachel Bawden; | acl | 2023-07-08 |
| 388 | On Evaluating Multilingual Compositional Generalization with Translated Datasets Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, we show that this entails critical semantic distortion. To address this limitation, we craft a faithful rule-based translation of the MCWQ dataset from English to Chinese and Japanese. |
Zi Wang; Daniel Hershcovich; | acl | 2023-07-08 |
| 389 | Understanding and Improving The Robustness of Terminology Constraints in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we study the robustness of two typical terminology translation methods: Placeholder (PH) and Code-Switch (CS), concerning (1) the number of constraints and (2) the target constraint length. |
HUAAO ZHANG et. al. | acl | 2023-07-08 |
| 390 | Neural Machine Translation Methods for Translating Text to Sign Language Glosses IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In our experiments, we improve the performance of the transformer-based models via (1) data augmentation, (2) semi-supervised Neural Machine Translation (NMT), (3) transfer learning and (4) multilingual NMT. |
Dele Zhu; Vera Czehmann; Eleftherios Avramidis; | acl | 2023-07-08 |
| 391 | Continual Knowledge Distillation for Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we propose a method called continual knowledge distillation to take advantage of existing translation models to improve one model of interest. |
Yuanchi Zhang; Peng Li; Maosong Sun; Yang Liu; | acl | 2023-07-08 |
| 392 | Extrinsic Evaluation of Machine Translation Metrics IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we investigate how useful MT metrics are at detecting the segment-level quality by correlating metrics with how useful the translations are for downstream task. |
Nikita Moghe; Tom Sherborne; Mark Steedman; Alexandra Birch; | acl | 2023-07-08 |
| 393 | Considerations for Meaningful Sign Language Machine Translation Based on Glosses IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we review recent works on neural gloss translation. |
Mathias M�ller; Zifan Jiang; Amit Moryossef; Annette Rios; Sarah Ebling; | acl | 2023-07-08 |
| 394 | Neural Machine Translation for Mathematical Formulae Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we perform the tasks of translating from LaTeX to Mathematica as well as from LaTeX to semantic LaTeX. |
Felix Petersen; Moritz Schubotz; Andre Greiner-Petter; Bela Gipp; | acl | 2023-07-08 |
| 395 | Learning Language-Specific Layers for Multilingual Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Language-Specific Transformer Layers (LSLs), which allow us to increase model capacity, while keeping the amount of computation and the number of parameters used in the forward pass constant. |
Telmo Pires; Robin Schmidt; Yi-Hsiu Liao; Stephan Peitz; | acl | 2023-07-08 |
| 396 | Songs Across Borders: Singable and Controllable Neural Lyric Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper bridges the singability quality gap by formalizing lyric translation into a constrained translation problem, converting theoretical guidance and practical techniques from translatology literature to prompt-driven NMT approaches, exploring better adaptation methods, and instantiating them to an English-Chinese lyric translation system. |
Longshen Ou; Xichu Ma; Min-Yen Kan; Ye Wang; | acl | 2023-07-08 |
| 397 | Multi-VALUE: A Framework for Cross-Dialectal English NLP IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a suite of resources for evaluating and achieving English dialect invariance. |
CALEB ZIEMS et. al. | acl | 2023-07-08 |
| 398 | Text Style Transfer Back-Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For natural inputs, BT brings only slight improvements and sometimes even adverse effects. To address this issue, we propose Text Style Transfer Back Translation (TST BT), which uses a style transfer to modify the source side of BT data. |
DAIMENG WEI et. al. | acl | 2023-07-08 |
| 399 | MultiTACRED: A Multilingual Version of The TAC Relation Extraction Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Relation extraction (RE) is a fundamental task in information extraction, whose extension to multilingual settings has been hindered by the lack of supervised resources comparable in size to large English datasets such as TACRED (Zhang et al. , 2017). To address this gap, we introduce the MultiTACRED dataset, covering 12 typologically diverse languages from 9 language families, which is created by machine-translating TACRED instances and automatically projecting their entity annotations. |
Leonhard Hennig; Philippe Thomas; Sebastian M�ller; | acl | 2023-07-08 |
| 400 | Tokenization Effect on Neural Machine Translation: An Experimental Investigation for English-Assamese Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Tokenization, as a research task, is mostly overlooked when dealing with machine translation as much emphasis is placed on modelling or data enhancement, not to speak for language … |
Mazida Akhtara Ahmed; Kishore Kashyap; Shikhar Kumar Sarma; | 2023 14th International Conference on Computing … | 2023-07-06 |
| 401 | To Be or Not to Be: A Translation Reception Study of A Literary Text Translated Into Dutch and Catalan Using Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This article presents the results of a study involving the reception of a fictional story by Kurt Vonnegut translated from English into Catalan and Dutch in three conditions: machine-translated (MT), post-edited (PE) and translated from scratch (HT). |
Ana Guerberof Arenas; Antonio Toral; | arxiv-cs.CL | 2023-07-05 |
| 402 | Simplification of Arabic Text: A Hybrid Approach Integrating Machine Translation and Transformer-based Lexical Model Related Papers Related Patents Related Grants Related Venues Related Experts View |
Suha Al-Thanyyan; Aqil M. Azmi; | J. King Saud Univ. Comput. Inf. Sci. | 2023-07-01 |
| 403 | X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Task-oriented dialogue research has mainly focused on a few popular languages like English and Chinese, due to the high dataset creation cost for a new language. |
MEHRAD MORADSHAHI et. al. | arxiv-cs.CL | 2023-06-30 |
| 404 | Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a simple yet efficient approach to adapt VLP to unseen languages using MPLM. |
Yasmine Karoui; Rémi Lebret; Negar Foroutan; Karl Aberer; | arxiv-cs.CL | 2023-06-29 |
| 405 | Learning Multilingual Expressive Speech Representation for Prosody Prediction Without Parallel Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We propose a method for speech-to-speech emotionpreserving translation that operates at the level of discrete speech units. Our approach relies on the use of multilingual emotion … |
J. Duret; Titouan Parcollet; Y. Estève; | ArXiv | 2023-06-29 |
| 406 | Scaling Laws for Multilingual Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we provide a large-scale empirical study of the scaling properties of multilingual neural machine translation models. |
Patrick Fernandes; Behrooz Ghorbani; Xavier Garcia; Markus Freitag; Orhan Firat; | icml | 2023-06-27 |
| 407 | The Unreasonable Effectiveness of Few-shot Learning for Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that with only 5 examples of high-quality translation data shown at inference, a transformer decoder-only model trained solely with self-supervised learning, is able to match specialized supervised state-of-the-art models as well as more general commercial translation systems. |
XAVIER GARCIA et. al. | icml | 2023-06-27 |
| 408 | Quality Estimation of Machine Translated Texts Based on Direct Evidence from Training Data Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we show that the parallel corpus used as training data for training the MT system holds direct clues for estimating the quality of translations produced by the MT system. |
Vibhuti Kumari; Narayana Murthy Kavi; | arxiv-cs.CL | 2023-06-27 |
| 409 | Constructing Multilingual Code Search Dataset Using Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this research, we create a multilingual code search dataset in four natural and four programming languages using a neural machine translation model. |
Ryo Sekizawa; Nan Duan; Shuai Lu; Hitomi Yanaka; | arxiv-cs.CL | 2023-06-27 |
| 410 | Prompting Neural Machine Translation with Translation Memories Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a simple but effective method to introduce TMs into neural machine translation (NMT) systems. |
ABUDUREXITI REHEMAN et. al. | aaai | 2023-06-26 |
| 411 | A Graph Fusion Approach for Cross-Lingual Machine Reading Comprehension Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel approach, which jointly models the cross-lingual alignment information and the mono-lingual syntax information using a graph. |
ZENAN XU et. al. | aaai | 2023-06-26 |
| 412 | Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for The Quality Assessment of Emotion Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on how current Machine Translation (MT) tools perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a framework proposed in this paper. |
Shenbin Qian; Constantin Orasan; Felix do Carmo; Qiuliang Li; Diptesh Kanojia; | arxiv-cs.CL | 2023-06-20 |
| 413 | BayLing: Bridging Cross-lingual Alignment and Instruction Following Through Interactive Translation for Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To minimize human workload, we propose to transfer the capabilities of language generation and instruction following from English to other languages through an interactive translation task. |
SHAOLEI ZHANG et. al. | arxiv-cs.CL | 2023-06-19 |
| 414 | Data Augmentation Via Back-translation for Aspect Term Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: We tackle Aspect Term Extraction (ATE), a task that automatically recognizes aspect terms conditioned on the under-standing of word-level semantics. Due to the capacity of … |
Qingting Xu; Yu Hong; Jiaxiang Chen; Jianmin Yao; Guodong Zhou; | 2023 International Joint Conference on Neural Networks … | 2023-06-18 |
| 415 | Sheffield’s Submission to The AmericasNLP Shared Task on Machine Translation Into Indigenous Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper we describe the University of Sheffield’s submission to the AmericasNLP 2023 Shared Task on Machine Translation into Indigenous Languages which comprises the translation from Spanish to eleven indigenous languages. |
Edward Gow-Smith; Danae Sánchez Villegas; | arxiv-cs.CL | 2023-06-16 |
| 416 | Discourse Representation Structure Parsing for Chinese Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We describe the pipeline of automatically collecting the linearized Chinese meaning representation data for sequential-to sequential neural networks. |
Chunliu Wang; Xiao Zhang; Johan Bos; | arxiv-cs.CL | 2023-06-16 |
| 417 | Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language Representations Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce Babel-ImageNet, a massively multilingual benchmark that offers (partial) translations of ImageNet labels to 100 languages, built without machine translation or manual annotation. |
Gregor Geigle; Radu Timofte; Goran Glavaš; | arxiv-cs.CL | 2023-06-14 |
| 418 | A Survey of Vision-Language Pre-training from The Lens of Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We summarize the common architectures, pre-training objectives, and datasets from literature and conjecture what further is needed to make progress on multimodal machine translation. |
Jeremy Gwinnup; Kevin Duh; | arxiv-cs.CL | 2023-06-12 |
| 419 | Rethinking Translation Memory Augmented Neural Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper rethinks translation memory augmented neural machine translation (TM-augmented NMT) from two perspectives, i.e., a probabilistic view of retrieval and the variance-bias … |
HONGKUN HAO et. al. | arxiv-cs.CL | 2023-06-12 |
| 420 | Textual Augmentation Techniques Applied to Low Resource Machine Translation: Case of Swahili Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work we investigate the impact of applying textual data augmentation tasks to low resource machine translation. |
Catherine Gitau; VUkosi Marivate; | arxiv-cs.CL | 2023-06-12 |
| 421 | Measuring Sentiment Bias in Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we explore how machine translation might introduce a bias in sentiments as classified by sentiment analysis models. |
KAI HARTUNG et. al. | arxiv-cs.CL | 2023-06-12 |
| 422 | A Benchmark Dataset and Evaluation Methodology for Chinese Zero Pronoun Translation Related Papers Related Patents Related Grants Related Venues Related Experts View |
MINGZHOU XU et. al. | Language Resources and Evaluation | 2023-06-10 |
| 423 | Good, But Not Always Fair: An Evaluation of Gender Bias for Three Commercial Machine Translation Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Consequently, analyses have been redirected to more nuanced aspects, intricate phenomena, as well as potential risks that may arise from the widespread use of MT tools. Along this line, this paper offers a meticulous assessment of three commercial MT systems – Google Translate, DeepL, and Modern MT – with a specific focus on gender translation and bias. |
Silvia Alma Piazzolla; Beatrice Savoldi; Luisa Bentivogli; | arxiv-cs.CL | 2023-06-09 |
| 424 | Assisting Language Learners: Automated Trans-Lingual Definition Generation Via Contrastive Prompt Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a novel task of Trans-Lingual Definition Generation (TLDG), which aims to generate definitions in another language, i.e., the native speaker’s language. |
HENGYUAN ZHANG et. al. | arxiv-cs.CL | 2023-06-09 |
| 425 | Improving Language Model Integration for Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Recently, some works on automatic speech recognition have demonstrated that, if the implicit language model is neutralized in decoding, further improvements can be gained when integrating an external language model. In this work, we transfer this concept to the task of machine translation and compare with the most prominent way of including additional monolingual data – namely back-translation. |
Christian Herold; Yingbo Gao; Mohammad Zeineldeen; Hermann Ney; | arxiv-cs.CL | 2023-06-08 |
| 426 | Twi Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: French is a strategically and economically important language in the regions where the African language Twi is spoken. However, only a very small proportion of Twi speakers in … |
Frederick Gyasi; Tim Schlippe; | Big Data Cogn. Comput. | 2023-06-08 |
| 427 | A Little Is Enough: Few-Shot Quality Estimation Based Corpus Filtering Improves Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: All the scripts and datasets utilized in this study will be publicly available. |
Akshay Batheja; Pushpak Bhattacharyya; | arxiv-cs.CL | 2023-06-06 |
| 428 | MCTS: A Multi-Reference Chinese Text Simplification Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we introduce MCTS, a multi-reference Chinese text simplification dataset. |
RUINING CHONG et. al. | arxiv-cs.CL | 2023-06-05 |
| 429 | Extract and Attend: Improving Entity Translation in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: When we humans encounter an unknown entity during translation, we usually first look up in a dictionary and then organize the entity translation together with the translations of other parts to form a smooth target sentence. Inspired by this translation process, we propose an Extract-and-Attend approach to enhance entity translation in NMT, where the translation candidates of source entities are first extracted from a dictionary and then attended to by the NMT model to generate the target sentence. |
ZIXIN ZENG et. al. | arxiv-cs.CL | 2023-06-03 |
| 430 | Speech Translation with Foundation Models and Optimal Transport: UPC at IWSLT23 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes the submission of the UPC Machine Translation group to the IWSLT 2023 Offline Speech Translation task. |
Ioannis Tsiamas; Gerard I. Gállego; José A. R. Fonollosa; Marta R. Costa-jussà; | arxiv-cs.CL | 2023-06-02 |
| 431 | Improving Polish to English Neural Machine Translation with Transfer Learning: Effects of Data Volume and Language Similarity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the impact of data volume and the use of similar languages on transfer learning in a machine translation task. |
Juuso Eronen; Michal Ptaszynski; Karol Nowakowski; Zheng Lin Chia; Fumito Masui; | arxiv-cs.CL | 2023-06-01 |
| 432 | Regressing Word and Sentence Embeddings for Low-Resource Neural Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: In recent years, neural machine translation (NMT) has achieved unprecedented performance in the automated translation of resource-rich languages. However, it has not yet managed … |
Inigo Jauregi Unanue; E. Z. Borzeshi; M. Piccardi; | IEEE Transactions on Artificial Intelligence | 2023-06-01 |
| 433 | Improved Cross-Lingual Transfer Learning For Automatic Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The goal of this work it to improve cross-lingual transfer learning in multilingual speech-to-text translation via semantic knowledge distillation. |
SAMEER KHURANA et. al. | arxiv-cs.CL | 2023-06-01 |
| 434 | How Does Pretraining Improve Discourse-Aware Translation? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the underlying reasons for their strong performance have not been well explained. To bridge this gap, we introduce a probing task to interpret the ability of PLMs to capture discourse relation knowledge. |
Zhihong Huang; Longyue Wang; Siyou Liu; Derek F. Wong; | arxiv-cs.CL | 2023-05-31 |
| 435 | Automatic Discrimination of Human and Neural Machine Translation in Multilingual Scenarios Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We tackle the task of automatically discriminating between human and machine translations. |
Malina Chichirau; Rik van Noord; Antonio Toral; | arxiv-cs.CL | 2023-05-31 |
| 436 | Translation-Enhanced Multilingual Text-to-Image Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: 2) We propose Ensemble Adapter (EnsAd), a novel parameter-efficient approach that learns to weigh and consolidate the multilingual text knowledge within the mTTI framework, mitigating the language gap and thus improving mTTI performance. |
Yaoyiran Li; Ching-Yun Chang; Stephen Rawls; Ivan Vulić; Anna Korhonen; | arxiv-cs.CL | 2023-05-30 |
| 437 | A Corpus for Sentence-level Subjectivity Detection on English News Articles IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We develop novel annotation guidelines for sentence-level subjectivity detection, which are not limited to language-specific cues. |
FRANCESCO ANTICI et. al. | arxiv-cs.CL | 2023-05-29 |
| 438 | An Open-Source Gloss-Based Baseline for Spoken to Signed Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present an open-source implementation of a text-to-gloss-to-pose-to-video pipeline approach, demonstrating conversion from German to Swiss German Sign Language, French to French Sign Language of Switzerland, and Italian to Italian Sign Language of Switzerland. |
AMIT MORYOSSEF et. al. | arxiv-cs.CL | 2023-05-28 |
| 439 | Neural Machine Translation with Dynamic Graph Convolutional Decoder Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, most previous works merely focus on leveraging the source syntax in the well-known encoder-decoder framework. In sharp contrast, this paper proposes an end-to-end translation architecture from the (graph \& sequence) structural inputs to the (graph \& sequence) outputs, where the target translation and its corresponding syntactic graph are jointly modeled and generated. |
Lei Li; Kai Fan; Lingyu Yang; Hongjia Li; Chun Yuan; | arxiv-cs.CL | 2023-05-28 |
| 440 | HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper presents HaVQA, the first multimodal dataset for visual question-answering (VQA) tasks in the Hausa language. |
SHANTIPRIYA PARIDA et. al. | arxiv-cs.CL | 2023-05-28 |
| 441 | Enhancing Translation for Indigenous Languages: Experiments with Multilingual Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper describes CIC NLP’s submission to the AmericasNLP 2023 Shared Task on machine translation systems for indigenous languages of the Americas. |
ATNAFU LAMBEBO TONJA et. al. | arxiv-cs.CL | 2023-05-27 |
| 442 | Do GPTs Produce Less Literal Translations? IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, there has been relatively little investigation on how such translations differ qualitatively from the translations generated by standard Neural Machine Translation (NMT) models. In this work, we investigate these differences in terms of the literalness of translations produced by the two systems. |
Vikas Raunak; Arul Menezes; Matt Post; Hany Hassan Awadalla; | arxiv-cs.CL | 2023-05-26 |
| 443 | Robustness of Multi-Source MT to Transcription Errors Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Automatic speech translation is sensitive to speech recognition errors, but in a multilingual scenario, the same content may be available in various languages via simultaneous interpreting, dubbing or subtitling. In this paper, we hypothesize that leveraging multiple sources will improve translation quality if the sources complement one another in terms of correct information they contain. |
Dominik Macháček; Peter Polák; Ondřej Bojar; Raj Dabre; | arxiv-cs.CL | 2023-05-26 |
| 444 | Disambiguated Lexically Constrained Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose disambiguated LCNMT (D-LCNMT) to solve the problem. |
JINPENG ZHANG et. al. | arxiv-cs.CL | 2023-05-26 |
| 445 | CODET: A Benchmark for Contrastive Dialectal Evaluation of Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Neural machine translation (NMT) systems exhibit limited robustness in handling source-side linguistic variations. Their performance tends to degrade when faced with even slight … |
Md Mahfuz Ibn Alam; Sina Ahmadi; Antonios Anastasopoulos; | arxiv-cs.CL | 2023-05-26 |
| 446 | What About “em”? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: As 3rd-person pronoun usage shifts to include novel forms, e.g., neopronouns, we need more research on identity-inclusive NLP. Exclusion is particularly harmful in one of the most … |
Anne Lauscher; Debora Nozza; Archie Crowley; E. Miltersen; Dirk Hovy; | Annual Meeting of the Association for Computational … | 2023-05-25 |
| 447 | What About Em? How Commercial Machine Translation Fails to Handle (Neo-)Pronouns Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Wrong pronoun translations can discriminate against marginalized groups, e.g., non-binary individuals (Dev et al., 2021). In this “reality check”, we study how three commercial MT systems translate 3rd-person pronouns. |
Anne Lauscher; Debora Nozza; Archie Crowley; Ehm Miltersen; Dirk Hovy; | arxiv-cs.CL | 2023-05-25 |
| 448 | MTCue: Learning Zero-Shot Control of Extra-Textual Attributes By Leveraging Unstructured Context in Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work introduces MTCue, a novel neural machine translation (NMT) framework that interprets all context (including discrete variables) as text. |
Sebastian Vincent; Robert Flynn; Carolina Scarton; | arxiv-cs.CL | 2023-05-25 |
| 449 | Cross-Lingual Knowledge Distillation for Answer Sentence Selection in Low-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose Cross-Lingual Knowledge Distillation (CLKD) from a strong English AS2 teacher as a method to train AS2 models for low-resource languages in the tasks without the need of labeled data for the target language. |
Shivanshu Gupta; Yoshitomo Matsubara; Ankit Chadha; Alessandro Moschitti; | arxiv-cs.CL | 2023-05-25 |
| 450 | Eliciting The Translation Ability of Large Language Models Via Multilingual Finetuning with Translation Instructions IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a detailed analysis by finetuning a multilingual pretrained language model, XGLM-7B, to perform multilingual translation following given instructions. |
Jiahuan Li; Hao Zhou; Shujian Huang; Shanbo Cheng; Jiajun Chen; | arxiv-cs.CL | 2023-05-24 |
| 451 | Textless Low-Resource Speech-to-Speech Translation With Unit Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We present a new framework for training textless low-resource speech-to-speech translation (S2ST) systems that only need dozens of hours of parallel speech data. |
Anuj Diwan; Anirudh Srinivasan; David Harwath; Eunsol Choi; | arxiv-cs.CL | 2023-05-24 |
| 452 | Leveraging GPT-4 for Automatic Translation Post-Editing IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we formalize the task of direct translation post-editing with Large Language Models (LLMs) and explore the use of GPT-4 to automatically post-edit NMT outputs across several language pairs. |
Vikas Raunak; Amr Sharaf; Yiren Wang; Hany Hassan Awadallah; Arul Menezes; | arxiv-cs.CL | 2023-05-24 |
| 453 | An Analysis of The Evaluation of The Translation Quality of Neural Machine Translation Application Systems Related Papers Related Patents Related Grants Related Venues Related Experts View |
Shanshan Liu; Wenxiao Zhu; | Appl. Artif. Intell. | 2023-05-23 |
| 454 | BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To better model the common semantics shared across texts and videos, we introduce a contrastive learning method in the cross-modal encoder. |
LIYAN KANG et. al. | arxiv-cs.CV | 2023-05-23 |
| 455 | WYWEB: A NLP Evaluation Benchmark For Classical Chinese Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: For the prosperity of the NLP community, in this paper, we introduce the WYWEB evaluation benchmark, which consists of nine NLP tasks in classical Chinese, implementing sentence classifi cation, sequence labeling, reading comprehension, and machine translation. |
Bo Zhou; Qianglong Chen; Tianyu Wang; Xiaomi Zhong; Yin Zhang; | arxiv-cs.CL | 2023-05-23 |
| 456 | CTQScorer: Combining Multiple Features for In-context Example Selection for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a general framework for combining different features influencing example selection. |
Aswanth Kumar; Ratish Puduppully; Raj Dabre; Anoop Kunchukuttan; | arxiv-cs.CL | 2023-05-23 |
| 457 | Improving Speech Translation By Fusing Speech and Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we harness the complementary strengths of speech and text, which are disparate modalities. |
WENBIAO YIN et. al. | arxiv-cs.CL | 2023-05-23 |
| 458 | Improving Isochronous Machine Translation with Target Factors and Auxiliary Counters Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce target factors in a transformer model to predict durations jointly with target language phoneme sequences. |
PROYAG PAL et. al. | arxiv-cs.CL | 2023-05-22 |
| 459 | Non-parametric, Nearest-neighbor-assisted Fine-tuning for Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Through qualitative analysis, we found particular improvements when it comes to translating grammatical relations or function words, which results in increased fluency of our model. |
Jiayi Wang; Ke Wang; Yuqi Zhang; Yu Zhao; Pontus Stenetorp; | arxiv-cs.CL | 2023-05-22 |
| 460 | Neural Machine Translation for Code Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper we survey the NMT for code generation literature, cataloging the variety of methods that have been explored according to input and output representations, model architectures, optimization techniques used, data sets, and evaluation methods. |
Dharma KC; Clayton T. Morrison; | arxiv-cs.CL | 2023-05-22 |
| 461 | Decomposed Prompting for Machine Translation Between Related Languages Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce DecoMT, a novel approach of few-shot prompting that decomposes the translation process into a sequence of word chunk translations. |
Ratish Puduppully; Anoop Kunchukuttan; Raj Dabre; Ai Ti Aw; Nancy F. Chen; | arxiv-cs.CL | 2023-05-22 |
| 462 | Is Translation Helpful? An Empirical Analysis of Cross-Lingual Transfer in Low-Resource Dialog Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A typical approach is to leverage off-the-shelf machine translation (MT) systems to utilize either the training corpus or developed models from high-resource languages. In this work, we investigate whether it is helpful to utilize MT at all in this task. |
Lei Shen; Shuai Yu; Xiaoyu Shen; | arxiv-cs.CL | 2023-05-21 |
| 463 | VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present our deployment-ready Speech-to-Speech Machine Translation (SSMT) system for English-Hindi, English-Marathi, and Hindi-Marathi language pairs. |
SHIVAM MHASKAR et. al. | arxiv-cs.CL | 2023-05-21 |
| 464 | ReSeTOX: Re-learning Attention Weights for Toxicity Mitigation in Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Our proposed method, ReSeTOX (REdo SEarch if TOXic), addresses the issue of Neural Machine Translation (NMT) generating translation outputs that contain toxic words not present in the input. |
Javier García Gilabert; Carlos Escolano; Marta R. Costa-Jussà; | arxiv-cs.CL | 2023-05-19 |
| 465 | HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we release an annotated dataset for the hallucination and omission phenomena covering 18 translation directions with varying resource levels and scripts. |
DAVID DALE et. al. | arxiv-cs.CL | 2023-05-19 |
| 466 | Viewing Knowledge Transfer in Multilingual Machine Translation Through A Representational Lens Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We argue that translation quality alone is not a sufficient metric for measuring knowledge transfer in multilingual neural machine translation. To support this claim, we introduce Representational Transfer Potential (RTP), which measures representational similarities between languages. |
David Stap; Vlad Niculae; Christof Monz; | arxiv-cs.CL | 2023-05-19 |
| 467 | NollySenti: Leveraging Transfer Learning and Machine Translation for Nigerian Movie Sentiment Classification Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we focus on the task of sentiment classification for cross domain adaptation. |
Iyanuoluwa Shode; David Ifeoluwa Adelani; Jing Peng; Anna Feldman; | arxiv-cs.CL | 2023-05-18 |
| 468 | DUB: Discrete Unit Back-translation for Speech Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: With DUB, the back-translation technique can successfully be applied on direct ST and obtains an average boost of 5.5 BLEU on MuST-C En-De/Fr/Es. |
Dong Zhang; Rong Ye; Tom Ko; Mingxuan Wang; Yaqian Zhou; | arxiv-cs.CL | 2023-05-18 |
| 469 | AlignAtt: Using Attention-based Audio-Translation Alignments As A Guide for Simultaneous Speech Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose AlignAtt, a novel policy for simultaneous ST (SimulST) that exploits the attention information to generate source-target alignments that guide the model during inference. |
Sara Papi; Marco Turchi; Matteo Negri; | arxiv-cs.CL | 2023-05-18 |
| 470 | Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To eliminate the rule-based nature of data creation, we instead propose using machine translation models to create gender-biased text from real gender-fair text via round-trip translation. |
Chantal Amrhein; Florian Schottmann; Rico Sennrich; Samuel Läubli; | arxiv-cs.CL | 2023-05-18 |
| 471 | On The Off-Target Problem of Zero-Shot Multilingual Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we find that failing in encoding discriminative target language signal will lead to off-target and a closer lexical distance (i.e., KL-divergence) between two languages’ vocabularies is related with a higher off-target rate. |
Liang Chen; Shuming Ma; Dongdong Zhang; Furu Wei; Baobao Chang; | arxiv-cs.CL | 2023-05-18 |
| 472 | Multilingual Event Extraction from Historical Newspaper Adverts Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce a new multilingual dataset in English, French, and Dutch composed of newspaper ads from the early modern colonial period reporting on enslaved people who liberated themselves from enslavement. |
Nadav Borenstein; Natalia da Silva Perez; Isabelle Augenstein; | arxiv-cs.CL | 2023-05-18 |
| 473 | Variable-length Neural Interlingua Representations for Zero-shot Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we introduce a novel method to enhance neural interlingua representations by making their length variable, thereby overcoming the constraint of fixed-length neural interlingua representations. |
Zhuoyuan Mao; Haiyue Song; Raj Dabre; Chenhui Chu; Sadao Kurohashi; | arxiv-cs.CL | 2023-05-17 |
| 474 | ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings Across Bengali and Five Other Low-Resource Languages IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this multicultural age, language translation is one of the most performed tasks, and it is becoming increasingly AI-moderated and automated. As a novel AI system, ChatGPT claims to be proficient in such translation tasks and in this paper, we put that claim to the test. |
Sourojit Ghosh; Aylin Caliskan; | arxiv-cs.CY | 2023-05-17 |
| 475 | Searching for Needles in A Haystack: On The Role of Incidental Bilingualism in PaLM’s Translation Capability Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We introduce a mixed-method approach to measure and understand incidental bilingualism at scale. |
Eleftheria Briakou; Colin Cherry; George Foster; | arxiv-cs.CL | 2023-05-17 |
| 476 | Searching for Needles in A Haystack: On The Role of Incidental Bilingualism in PaLM’s Translation Capability IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Large, multilingual language models exhibit surprisingly good zero- or few-shot machine translation capabilities, despite having never seen the intentionally-included translation … |
Eleftheria Briakou; Colin Cherry; George F. Foster; | Annual Meeting of the Association for Computational … | 2023-05-17 |
| 477 | Progressive Translation: Improving Domain Robustness of Neural Machine Translation with Intermediate Sequences Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Borrowing techniques from Statistical Machine Translation, we propose intermediate signals which are intermediate sequences from the source-like structure to the target-like structure. |
Chaojun Wang; Yang Liu; Wai Lam; | arxiv-cs.CL | 2023-05-16 |
| 478 | The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided By Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Motivated particularly by the task of cross-lingual SLU, we demonstrate that the task of speech translation (ST) is a good means of pretraining speech models for end-to-end SLU on both intra- and cross-lingual scenarios. |
Mutian He; Philip N. Garner; | arxiv-cs.CL | 2023-05-16 |
| 479 | XPQA: Cross-Lingual Product Question Answering Across 12 Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: While existing work on PQA focuses mainly on English, in practice there is need to support multiple customer languages while leveraging product information available in English. To study this practical industrial task, we present xPQA, a large-scale annotated cross-lingual PQA dataset in 12 languages across 9 branches, and report results in (1) candidate ranking, to select the best English candidate containing the information to answer a non-English question; and (2) answer generation, to generate a natural-sounding non-English answer based on the selected English candidate. |
Xiaoyu Shen; Akari Asai; Bill Byrne; Adrià de Gispert; | arxiv-cs.CL | 2023-05-16 |
| 480 | Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Secondly, the knowledge is largely covered by the golden information due to the fact that most top-1 predictions of teachers overlap with ground-truth tokens, which further restricts the potential of KD. To address these issues, we propose a novel method named \textbf{T}op-1 \textbf{I}nformation \textbf{E}nhanced \textbf{K}nowledge \textbf{D}istillation (TIE-KD). |
SONGMING ZHANG et. al. | arxiv-cs.CL | 2023-05-14 |
| 481 | PESTS: Persian_English Cross Lingual Corpus for Semantic Textual Similarity Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this article, the corpus of semantic textual similarity between sentences in Persian and English languages has been produced for the first time by using linguistic experts. |
Mohammad Abdous; Poorya Piroozfar; Behrouz Minaei Bidgoli; | arxiv-cs.CL | 2023-05-13 |
| 482 | Improving Zero-shot Multilingual Neural Machine Translation By Leveraging Cross-lingual Consistency Regularization IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper introduces a cross-lingual consistency regularization, CrossConST, to bridge the representation gap among different languages and boost zero-shot translation performance. |
Pengzhi Gao; Liwen Zhang; Zhongjun He; Hua Wu; Haifeng Wang; | arxiv-cs.CL | 2023-05-12 |
| 483 | Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present Perturbation-based QE – a word-level Quality Estimation approach that works simply by analyzing MT system output on perturbed input source sentences. |
Tu Anh Dinh; Jan Niehues; | arxiv-cs.CL | 2023-05-12 |
| 484 | Chain-of-Dictionary Prompting Elicits Translation in Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To this end, we present a novel method, CoD, which augments LLMs with prior knowledge with the chains of multilingual dictionaries for a subset of input words to elicit translation abilities for LLMs. |
HONGYUAN LU et. al. | arxiv-cs.CL | 2023-05-11 |
| 485 | Subword Segmental Machine Translation: Unifying Segmentation and Target Sentence Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To use SSMT during inference we propose dynamic decoding, a text generation algorithm that adapts segmentations as it generates translations. |
Francois Meyer; Jan Buys; | arxiv-cs.CL | 2023-05-11 |
| 486 | How Good Are Commercial Large Language Models on African Languages? Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We present a preliminary analysis of commercial large language models on two tasks (machine translation and text classification) across eight African languages, spanning different language families and geographical areas. |
Jessica Ojo; Kelechi Ogueji; | arxiv-cs.CL | 2023-05-10 |
| 487 | PriGen: Towards Automated Translation of Android Applications’ Code to Privacy Captions Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Previous work has attempted to help developers create privacy notices through a questionnaire or predefined templates. In this paper, we propose a novel approach and a framework, called PriGen, that extends these prior work. |
Vijayanta Jain; Sanonda Datta Gupta; Sepideh Ghanavati; Sai Teja Peddinti; | arxiv-cs.SE | 2023-05-10 |
| 488 | Multi-Teacher Knowledge Distillation For Text Image Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel Multi-Teacher Knowledge Distillation (MTKD) method to effectively distillate knowledge into the end-to-end TIMT model from the pipeline model. |
CONG MA et. al. | arxiv-cs.CL | 2023-05-09 |
| 489 | CharSpan: Utilizing Lexical Similarity to Enable Zero-Shot Machine Translation for Extremely Low-resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, existing subword-based neural MT models do not explicitly harness this lexical similarity, as they only implicitly align HRL and ELRL latent embedding space. To overcome this limitation, we propose a novel, CharSpan, approach based on ‘character-span noise augmentation’ into the training data of HRL. |
Kaushal Kumar Maurya; Rahul Kejriwal; Maunendra Sankar Desarkar; Anoop Kunchukuttan; | arxiv-cs.CL | 2023-05-09 |
| 490 | Text-image Matching for Multi-model Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View |
Xiayang Shi; Zhenqiang Yu; Xuhui Wang; Yijun Li; Yufeng Niu; | The Journal of Supercomputing | 2023-05-09 |
| 491 | MultiTACRED: A Multilingual Version of The TAC Relation Extraction Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Relation extraction (RE) is a fundamental task in information extraction, whose extension to multilingual settings has been hindered by the lack of supervised resources comparable in size to large English datasets such as TACRED (Zhang et al., 2017). To address this gap, we introduce the MultiTACRED dataset, covering 12 typologically diverse languages from 9 language families, which is created by machine-translating TACRED instances and automatically projecting their entity annotations. |
Leonhard Hennig; Philippe Thomas; Sebastian Möller; | arxiv-cs.CL | 2023-05-08 |
| 492 | Label-Free Multi-Domain Machine Translation with Stage-wise Training Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we propose a label-free multi-domain machine translation model which requires only a few or no domain-annotated data in training and no domain labels in inference. |
Fan Zhang; Mei Tu; Sangha Kim; Song Liu; Jinyao Yan; | arxiv-cs.CL | 2023-05-06 |
| 493 | Exploring Human-Like Translation Strategy with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Compared to typical machine translation that focuses solely on source-to-target mapping, LLM-based translation can potentially mimic the human translation process which might take preparatory steps to ensure high-quality translation. This work explores this possibility by proposing the MAPS framework, which stands for Multi-Aspect Prompting and Selection. |
ZHIWEI HE et. al. | arxiv-cs.CL | 2023-05-06 |
| 494 | In-context Learning As Maintaining Coherency: A Study of On-the-fly Machine Translation Using Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: The phenomena of in-context learning has typically been thought of as learning from examples. In this work which focuses on Machine Translation, we present a perspective of in-context learning as the desired generation task maintaining coherency with its context, i.e., the prompt examples. |
Suzanna Sia; Kevin Duh; | arxiv-cs.CL | 2023-05-05 |
| 495 | Learning Language-Specific Layers for Multilingual Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we introduce Language-Specific Transformer Layers (LSLs), which allow us to increase model capacity, while keeping the amount of computation and the number of parameters used in the forward pass constant. |
Telmo Pessoa Pires; Robin M. Schmidt; Yi-Hsiu Liao; Stephan Peitz; | arxiv-cs.CL | 2023-05-04 |
| 496 | Unified Model Learning for Various Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Although the dataset-specific models have achieved impressive performance, it is cumbersome as each dataset demands a model to be designed, trained, and stored. In this work, we aim to unify these translation tasks into a more general setting. |
YUNLONG LIANG et. al. | arxiv-cs.CL | 2023-05-04 |
| 497 | Investigating Lexical Sharing in Multilingual Machine Translation for Indian Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we investigate lexical sharing in multilingual machine translation (MT) from Hindi, Gujarati, Nepali into English. |
Sonal Sannigrahi; Rachel Bawden; | arxiv-cs.CL | 2023-05-04 |
| 498 | Evaluating The Efficacy of Length-Controllable Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We find that BLEURT and COMET have the highest correlation with human evaluation and are most suitable as evaluation metrics for length-controllable machine translation. |
HAO CHENG et. al. | arxiv-cs.CL | 2023-05-03 |
| 499 | Shared Latent Space By Both Languages in Non-Autoregressive Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel latent variable modeling that integrates a dual reconstruction perspective and an advanced hierarchical latent modeling with a shared intermediate latent space across languages. |
DongNyeong Heo; Heeyoul Choi; | arxiv-cs.CL | 2023-05-02 |
| 500 | SLTUNET: A Simple Unified Model for Sign Language Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose SLTUNET, a simple unified neural model designed to support multiple SLTrelated tasks jointly, such as sign-to-gloss, gloss-to-text and sign-to-text translation. |
Biao Zhang; Mathias Müller; Rico Sennrich; | arxiv-cs.CL | 2023-05-02 |
| 501 | English-Assamese Neural Machine Translation Using Prior Alignment and Pre-trained Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View |
SAHINUR RAHMAN LASKAR et. al. | Comput. Speech Lang. | 2023-05-01 |
| 502 | Metamorphic Testing of Machine Translation Models Using Back Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine translation software has been widely adopted in recent years. The recent advance in deep learning research has massively improved the accuracy and fluency of the … |
Wentao Gao; Jiayuan He; Van-Thuan Pham; | 2023 IEEE/ACM International Workshop on Deep Learning for … | 2023-05-01 |
| 503 | Low-Resourced Machine Translation for Senegalese Wolof Language Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we present a parallel Wolof/French corpus of 123,000 sentences on which we conducted experiments on machine translation models based on Recurrent Neural Networks (RNN) in different data configurations. |
Derguene Mbaye; Moussa Diallo; Thierno Ibrahima Diop; | arxiv-cs.CL | 2023-04-30 |
| 504 | Targeted Adversarial Attacks Against Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new targeted adversarial attack against NMT models. |
S. Sadrizadeh; A. D. Aghdam; L. Dolamic; P. Frossard; | icassp | 2023-04-27 |
| 505 | Lost In Translation: Generating Adversarial Examples Robust to Round-Trip Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a comprehensive study on the robustness of current text adversarial attacks to round-trip translation. |
N. Bhandari; P. -Y. Chen; | icassp | 2023-04-27 |
| 506 | LEAPT: Learning Adaptive Prefix-to-Prefix Translation For Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by strategies utilized by human interpreters and wait policies, we propose a novel adaptive prefix-to-prefix training policy called LEAPT, which allows our machine translation model to learn how to translate source sentence prefixes and make use of the future context. |
L. Lin; S. Li; X. Shi; | icassp | 2023-04-27 |
| 507 | Rethinking The Reasonability of The Test Set for Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we manually annotate a monotonic test set based on the MuST-C English-Chinese test set, denoted as SiMuST-C. |
M. LIU et. al. | icassp | 2023-04-27 |
| 508 | Improving Speech-to-Speech Translation Through Unlabeled Text Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We propose an effective way to utilize the massive existing unlabeled text from different languages to create a large amount of S2ST data to improve S2ST performance by applying various acoustic effects to the generated synthetic data. |
X. -P. NGUYEN et. al. | icassp | 2023-04-27 |
| 509 | M3ST: Mix at Three Levels for Speech Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Mix at three levels for Speech Translation (M3ST) method to increase the diversity of the augmented training corpus. |
X. CHENG et. al. | icassp | 2023-04-27 |
| 510 | A Corpus-Based Auto-encoder-and-Decoder Machine Translation Using Deep Neural Network for Translation from English to Telugu Language Related Papers Related Patents Related Grants Related Venues Related Experts View |
Mohan Mahanty; B. Vamsi; Dasari Madhavi; | SN Computer Science | 2023-04-26 |
| 511 | Escaping The Sentence-level Paradigm in Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Much work in document-context machine translation exists, but for various reasons has been unable to catch hold. This paper suggests a path out of this rut by addressing three impediments at once: what architectures should we use? |
Matt Post; Marcin Junczys-Dowmunt; | arxiv-cs.CL | 2023-04-25 |
| 512 | NAIST-SIC-Aligned: An Aligned English-Japanese Simultaneous Interpretation Corpus Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we aim to fill in the gap by introducing NAIST-SIC-Aligned, which is an automatically-aligned parallel English-Japanese SI dataset. |
JINMING ZHAO et. al. | arxiv-cs.CL | 2023-04-23 |
| 513 | NAIST-SIC-Aligned: Automatically-Aligned English-Japanese Simultaneous Interpretation Corpus Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: It remains a question that how simultaneous interpretation (SI) data affects simultaneous machine translation (SiMT). Research has been limited due to the lack of a large-scale … |
JINMING ZHAO et. al. | ArXiv | 2023-04-23 |
| 514 | Lost in Translationese? Reducing Translation Effect Using Abstract Meaning Representation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We compare our AMR-based approach against three other techniques based on machine translation or paraphrase generation. |
Shira Wein; Nathan Schneider; | arxiv-cs.CL | 2023-04-22 |
| 515 | Improving Speech Translation By Cross-Modal Multi-Grained Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: However, the final model often performs worse on the MT task than the MT model trained alone, which means that the knowledge transfer ability of this method is also limited. To deal with these problems, we propose the FCCL (Fine- and Coarse- Granularity Contrastive Learning) approach for E2E-ST, which makes explicit knowledge transfer through cross-modal multi-grained contrastive learning. |
HAO ZHANG et. al. | arxiv-cs.CL | 2023-04-20 |
| 516 | The EBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We introduce the eBible corpus: a dataset containing 1009 translations of portions of the Bible with data in 833 different languages across 75 language families. |
VESA AKERMAN et. al. | arxiv-cs.CL | 2023-04-19 |
| 517 | An Empirical Study of Leveraging Knowledge Distillation for Compressing Multilingual Neural Machine Translation Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: However, works focusing on distilling knowledge from large multilingual neural machine translation (MNMT) models into smaller ones are practically nonexistent, despite the popularity and superiority of MNMT. This paper bridges this gap by presenting an empirical investigation of knowledge distillation for compressing MNMT models. |
Varun Gumma; Raj Dabre; Pratyush Kumar; | arxiv-cs.CL | 2023-04-18 |
| 518 | Neural Machine Translation For Low Resource Languages Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The goal of this paper is to investigate the realm of low resource languages and build a Neural Machine Translation model to achieve state-of-the-art results. |
Vakul Goyle; Parvathy Krishnaswamy; Kannan Girija Ravikumar; Utsa Chattopadhyay; Kartikay Goyle; | arxiv-cs.CL | 2023-04-16 |
| 519 | TransDocs: Optical Character Recognition with Word to Word Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, I have shown comparative study for pre-trained OCR while using deep learning model using LSTM-based seq2seq architecture with attention for machine translation. |
Abhishek Bamotra; Phani Krishna Uppala; | arxiv-cs.CV | 2023-04-15 |
| 520 | Learning Homographic Disambiguation Representation for Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel approach to tackle homographic issues of NMT in the latent space. |
Weixuan Wang; Wei Peng; Qun Liu; | arxiv-cs.CL | 2023-04-12 |
| 521 | Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions: 1) How well do LLMs perform in translating massive languages? |
WENHAO ZHU et. al. | arxiv-cs.CL | 2023-04-10 |
| 522 | RISC: Generating Realistic Synthetic Bilingual Insurance Contract Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This paper presents RISC, an open-source Python package data generator (https://github.com/GRAAL-Research/risc). |
David Beauchemin; Richard Khoury; | arxiv-cs.CL | 2023-04-09 |
| 523 | How to Design Translation Prompts for ChatGPT: An Empirical Study IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Thus, in this paper, we explore how to assist machine translation with ChatGPT. |
Yuan Gao; Ruili Wang; Feng Hou; | arxiv-cs.CL | 2023-04-04 |
| 524 | LAHM : Large Annotated Dataset for Multi-Domain and Multilingual Hate Speech Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we present a new multilingual hate speech analysis dataset for English, Hindi, Arabic, French, German and Spanish languages for multiple domains across hate speech – Abuse, Racism, Sexism, Religious Hate and Extremism. |
Ankit Yadav; Shubham Chandel; Sushant Chatufale; Anil Bandhakavi; | arxiv-cs.CL | 2023-04-03 |
| 525 | LAHM : Large Annotated Dataset for Multilingual & Multi-Domain Hate Speech Identification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual hate speech … |
Ankit Yadav; Shubham Chandel; Sushant Chatufale; Anil Bandhakavi; | ArXiv | 2023-04-03 |
| 526 | A Neural Attention-Based Encoder-Decoder Approach for English to Bangla Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Machine translation (MT) is the process of translating text from one language to another using bilingual data sets and grammatical rules. Recent works in the field of MT have … |
Abdullah Al Shiam; S. M. Redwan; Humaun Kabir; Jungpil Shin; | Comput. Sci. J. Moldova | 2023-04-01 |
| 527 | $\varepsilon$ KÚ Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: This paper investigates the performance of massively multilingual neural machine translation (NMT) systems in translating Yor\`ub\’a greetings ($\varepsilon$ k\’u [MASK]), which are a big part of Yor\`ub\’a language and culture, into English. To evaluate these models, we present IkiniYor\`ub\’a, a Yor\`ub\’a-English translation dataset containing some Yor\`ub\’a greetings, and sample use cases. |
Idris Akinade; Jesujoba Alabi; David Adelani; Clement Odoje; Dietrich Klakow; | arxiv-cs.CL | 2023-03-31 |
| 528 | Varepsilon Kú Mask: Integrating Yorùbá Cultural Greetings Into Machine Translation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: This paper investigates the performance of massively multilingual neural machine translation (NMT) systems in translating Yorùbá greetings (kú mask), which are a big part of … |
Idris Akinade; Jesujoba Oluwadara Alabi; David Ifeoluwa Adelani; Clement Odoje; D. Klakow; | ArXiv | 2023-03-31 |
| 529 | Sentiment Analysis of Multilingual Dataset of Bahraini Dialects, Arabic, and English Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Sentiment analysis is an application of natural language processing (NLP) that requires a machine learning algorithm and a dataset. In some cases, the dataset availability is … |
Thuraya Omran; Baraa T. Sharef; C. Grosan; Yongming Li; | Data | 2023-03-30 |
| 530 | Hallucinations in Large Multilingual Translation Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Existing research on hallucinations has primarily focused on small bilingual models trained on high-resource languages, leaving a gap in our understanding of hallucinations in massively multilingual models across diverse translation scenarios. In this work, we fill this gap by conducting a comprehensive analysis on both the M2M family of conventional neural machine translation models and ChatGPT, a general-purpose large language model~(LLM) that can be prompted for translation. |
NUNO M. GUERREIRO et. al. | arxiv-cs.CL | 2023-03-28 |
| 531 | Translate The Beauty in Songs: Jointly Learning to Align Melody and Translate Lyrics Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose Lyrics-Melody Translation with Adaptive Grouping (LTAG), a holistic solution to automatic song translation by jointly modeling lyrics translation and lyrics-melody alignment. |
CHENGXI LI et. al. | arxiv-cs.CL | 2023-03-27 |
| 532 | Bilex Rx: Lexical Data Augmentation for Massively Multilingual Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We test the efficacy of bilingual lexica in a real-world set-up, on 200-language translation models trained on web-crawled text. We present several findings: (1) using lexical data augmentation, we demonstrate sizable performance gains for unsupervised translation; (2) we compare several families of data augmentation, demonstrating that they yield similar improvements, and can be combined for even greater improvements; (3) we demonstrate the importance of carefully curated lexica over larger, noisier ones, especially with larger models; and (4) we compare the efficacy of multilingual lexicon data versus human-translated parallel data. |
Alex Jones; Isaac Caswell; Ishank Saxena; Orhan Firat; | arxiv-cs.CL | 2023-03-27 |
| 533 | Linguistically Informed ChatGPT Prompts to Enhance Japanese-Chinese Machine Translation: A Case Study on Attributive Clauses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Present-day machine translation tools often fail to accurately translate attributive clauses from Japanese to Chinese. In light of this, this paper investigates the linguistic problem underlying such difficulties, namely how does the semantic role of the modified noun affect the selection of translation patterns for attributive clauses, from a linguistic perspective. |
Wenshi Gu; | arxiv-cs.CL | 2023-03-27 |
| 534 | Towards Making The Most of ChatGPT for Machine Translation IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we aim to further mine ChatGPT’s translation ability by revisiting several aspects: temperature, task information, and domain information, and correspondingly propose an optimal temperature setting and two (simple but effective) prompts: Task-Specific Prompts (TSP) and Domain-Specific Prompts (DSP). |
KEQIN PENG et. al. | arxiv-cs.CL | 2023-03-23 |
| 535 | Selective Data Augmentation for Robust Speech Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose to use an e2e architecture for English-Hindi (en-hi) ST. We use two imperfect machine translation (MT) services to translate Libri-trans en text into hi text. |
Rajul Acharya; Ashish Panda; Sunil Kumar Kopparapu; | arxiv-cs.CL | 2023-03-22 |
| 536 | LEAPT: Learning Adaptive Prefix-to-prefix Translation For Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Inspired by strategies utilized by human interpreters and wait policies, we propose a novel adaptive prefix-to-prefix training policy called LEAPT, which allows our machine translation model to learn how to translate source sentence prefixes and make use of the future context. |
Lei Lin; Shuangtao Li; Xiaodong Shi; | arxiv-cs.CL | 2023-03-21 |
| 537 | Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: A contributing factor to this problem is that NMT models trained with the one-to-one paradigm struggle to handle the source diversity phenomenon, where inputs with the same meaning can be expressed differently. In this work, we treat this problem as a bilevel optimization problem and present a consistency-aware meta-learning (CAML) framework derived from the model-agnostic meta-learning (MAML) algorithm to address it. |
Rongxiang Weng; Qiang Wang; Wensen Cheng; Changfeng Zhu; Min Zhang; | arxiv-cs.CL | 2023-03-20 |
| 538 | Translate Your Gibberish: Black-box Adversarial Attack on Machine Translation Systems Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this work, we present a simple approach to fool state-of-the-art machine translation tools in the task of translation from Russian to English and vice versa. |
Andrei Chertkov; Olga Tsymboi; Mikhail Pautov; Ivan Oseledets; | arxiv-cs.CL | 2023-03-20 |
| 539 | ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: To relax the dependency on labeled data of downstream tasks, we propose an intuitive and effective zero-shot learning framework, ZeroNLG, which can deal with multiple NLG tasks, including image-to-text (image captioning), video-to-text (video captioning), and text-to-text (neural machine translation), across English, Chinese, German, and French within a unified framework. |
BANG YANG et. al. | arxiv-cs.CL | 2023-03-11 |
| 540 | A Multi-stack RNN-based Neural Machine Translation Model for English to Pakistan Sign Language Translation Related Papers Related Patents Related Grants Related Venues Related Experts View |
U. Farooq; Mohd Shafry Mohd Rahim; Adnan Abid; | Neural Computing and Applications | 2023-03-11 |
| 541 | MixSpeech: Cross-Modality Self-Learning with Audio-Visual Stream Mixup for Visual Speech Translation and Recognition IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Nonetheless, visual speech is not as distinguishable as audio speech, making it difficult to develop a mapping from source speech phonemes to the target language text. To address this issue, we propose MixSpeech, a cross-modality self-learning framework that utilizes audio speech to regularize the training of visual speech tasks. |
XIZE CHENG et. al. | arxiv-cs.CV | 2023-03-09 |
| 542 | GATE: A Challenge Set for Gender-Ambiguous Translation Examples IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Recent work has led to the development of gender rewriters that generate alternative gender translations on such ambiguous inputs, but such systems are plagued by poor linguistic coverage. To encourage better performance on this task we present and release GATE, a linguistically diverse corpus of gender-ambiguous source sentences along with multiple alternative target language translations. |
Spencer Rarrick; Ranjita Naik; Varun Mathur; Sundar Poudel; Vishal Chowdhary; | arxiv-cs.CL | 2023-03-07 |
| 543 | Exploiting Language Relatedness in Machine Translation Through Domain Adaptation Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In order to tackle the challenges faced by MT, we present a novel approach of using a scaled similarity score of sentences, especially for related languages based on a 5-gram KenLM language model with Kneser-ney smoothing technique for filtering in-domain data from out-of-domain corpora that boost the translation quality of MT. Furthermore, we employ other domain adaptation techniques such as multi-domain, fine-tuning and iterative back-translation approach to compare our novel approach on the Hindi-Nepali language pair for NMT and SMT. |
Amit Kumar; Rupjyoti Baruah; Ajay Pratap; Mayank Swarnkar; Anil Kumar Singh; | arxiv-cs.CL | 2023-03-03 |
| 544 | Rethinking The Reasonability of The Test Set for Simultaneous Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we manually annotate a monotonic test set based on the MuST-C English-Chinese test set, denoted as SiMuST-C. |
MENGGE LIU et. al. | arxiv-cs.CL | 2023-03-02 |
| 545 | Targeted Adversarial Attacks Against Neural Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we propose a new targeted adversarial attack against NMT models. |
Sahar Sadrizadeh; AmirHossein Dabiri Aghdam; Ljiljana Dolamic; Pascal Frossard; | arxiv-cs.CL | 2023-03-02 |
| 546 | Federated Nearest Neighbor Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel federated nearest neighbor (FedNN) machine translation framework that, instead of multi-round model-based interactions, leverages one-round memorization-based interaction to share knowledge across different clients to build low-overhead privacy-preserving systems. |
YICHAO DU et. al. | arxiv-cs.CL | 2023-02-23 |
| 547 | Exploring The Potential of Machine Translation for Generating Named Entity Datasets: A Case Study Between Persian and English Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This study focuses on the generation of Persian named entity datasets through the application of machine translation on English datasets. |
Amir Sartipi; Afsaneh Fatemi; | arxiv-cs.CL | 2023-02-19 |
| 548 | Zero and Few-Shot Localization of Task-Oriented Dialogue Agents with A Distilled Representation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We propose automatic methods that use ToD training data in a source language to build a high-quality functioning dialogue agent in another target language that has no training data (i.e. zero-shot) or a small training set (i.e. few-shot). |
Mehrad Moradshahi; Sina J. Semnani; Monica S. Lam; | arxiv-cs.CL | 2023-02-18 |
| 549 | How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation IF:5 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we present a comprehensive evaluation of GPT models for machine translation, covering various aspects such as quality of different GPT models in comparison with state-of-the-art research and commercial systems, effect of prompting strategies, robustness towards domain shifts and document-level translation. |
AMR HENDY et. al. | arxiv-cs.CL | 2023-02-17 |
| 550 | Evaluating and Improving The Coreference Capabilities of Machine Translation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this work, we ask: \emph{How well do MT models learn coreference resolution from implicit signal?} |
Asaf Yehudai; Arie Cattan; Omri Abend; Gabriel Stanovsky; | arxiv-cs.CL | 2023-02-16 |
| 551 | Document Flattening: Beyond Concatenating Context for Document-Level Neural Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We conduct comprehensive experiments and analyses on three benchmark datasets for English-German translation, and validate the effectiveness of two variants of DocFlat. |
Minghao Wu; George Foster; Lizhen Qu; Gholamreza Haffari; | arxiv-cs.CL | 2023-02-15 |
| 552 | Encoding Sentence Position in Context-Aware Neural Machine Translation with Concatenation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: We compare various methods to encode sentence positions into token representations, including novel methods. |
Lorenzo Lupo; Marco Dinarelli; Laurent Besacier; | arxiv-cs.CL | 2023-02-13 |
| 553 | Language-Aware Multilingual Machine Translation with Self-Supervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: Finally, we apply intra-distillation to this co-training approach. Combining these two approaches significantly improves MMT performance, outperforming three state-of-the-art SSL methods by a large margin, e.g., 11.3\% and 3.7\% improvement on an 8-language and a 15-language benchmark compared with MASS, respectively |
Haoran Xu; Jean Maillard; Vedanuj Goswami; | arxiv-cs.CL | 2023-02-09 |
| 554 | Learning Translation Quality Evaluation on Low Resource Languages from Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Training such metrics requires data which can be expensive and difficult to acquire, particularly for lower-resource languages. We show how knowledge can be distilled from Large Language Models (LLMs) to improve upon such learned metrics without requiring human annotators, by creating synthetic datasets which can be mixed into existing datasets, requiring only a corpus of text in the target language. |
Amirkeivan Mohtashami; Mauro Verzetti; Paul K. Rubenstein; | arxiv-cs.CL | 2023-02-07 |
| 555 | The Unreasonable Effectiveness of Few-shot Learning for Machine Translation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We show that with only 5 examples of high-quality translation data shown at inference, a transformer decoder-only model trained solely with self-supervised learning, is able to match specialized supervised state-of-the-art models as well as more general commercial translation systems. |
XAVIER GARCIA et. al. | arxiv-cs.CL | 2023-02-02 |
| 556 | Code Translation with Compiler Representations IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: In this paper, we leverage low-level compiler intermediate representations (IR) code translation. |
MARC SZAFRANIEC et. al. | iclr | 2023-02-01 |
| 557 | An Evaluation of Persian-English Machine Translation Datasets with Transformers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Nowadays, many researchers are focusing their attention on the subject of machine translation (MT). However, Persian machine translation has remained unexplored despite a vast … |
Amir Sartipi; Meghdad Dehghan; Afsaneh Fatemi; | arxiv-cs.CL | 2023-02-01 |
| 558 | Attention Link: An Efficient Attention-Based Low Resource Machine Translation Architecture Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we propose a novel architecture named as attention link (AL) to help improve transformer models’ performance, especially in low training resources. |
Zeping Min; | arxiv-cs.CL | 2023-02-01 |
| 559 | Adaptive Machine Translation with Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This work aims to investigate how we can utilize in-context learning to improve real-time adaptive MT. Our extensive experiments show promising results at translation time. |
Yasmin Moslem; Rejwanul Haque; John D. Kelleher; Andy Way; | arxiv-cs.CL | 2023-01-30 |
| 560 | KG-BERTScore: Incorporating Knowledge Graph Into BERTScore for Reference-Free Machine Translation Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we incorporate multilingual knowledge graph into BERTScore and propose a metric named KG-BERTScore, which linearly combines the results of BERTScore and bilingual named entity matching for reference-free machine translation evaluation. |
ZHANGLIN WU et. al. | arxiv-cs.CL | 2023-01-30 |
| 561 | Gender Neutralization for An Inclusive Machine Translation: from Theoretical Foundations to Open Challenges Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a goal to be achieved by machine translation (MT) models, which have been found to perpetuate gender bias and discrimination. |
Andrea Piergentili; Dennis Fucci; Beatrice Savoldi; Luisa Bentivogli; Matteo Negri; | arxiv-cs.CL | 2023-01-24 |
| 562 | Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine IF:4 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: This report provides a preliminary evaluation of ChatGPT for machine translation, including translation prompt, multilingual translation, and translation robustness. |
WENXIANG JIAO et. al. | arxiv-cs.CL | 2023-01-20 |
| 563 | Malayalam Natural Language Processing: Challenges in Building A Phrase-Based Statistical Machine Translation System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Abstract: Statistical Machine Translation (SMT) is a preferred Machine Translation approach to convert the text in a specific language into another by automatically learning translations … |
M. Sebastian; G. Santhosh Kumar; | ACM Transactions on Asian and Low-Resource Language … | 2023-01-19 |
| 564 | Improving Machine Translation with Phrase Pair Injection and Corpus Filtering IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we show that the combination of Phrase Pair Injection and Corpus Filtering boosts the performance of Neural Machine Translation (NMT) systems. |
Akshay Batheja; Pushpak Bhattacharyya; | arxiv-cs.CL | 2023-01-19 |
| 565 | Machine Translation for Accessible Multi-Language Text Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we aim to leverage those very advances to demonstrate that multi-language analysis is currently accessible to all computational scholars. |
Edward W. Chew; William D. Weisman; Jingying Huang; Seth Frey; | arxiv-cs.CL | 2023-01-19 |
| 566 | Understanding and Detecting Hallucinations in Neural Machine Translation Via Model Introspection IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Abstract: Neural sequence generation models are known to hallucinate, by producing outputs that are unrelated to the source text. These hallucinations are potentially harmful, yet it … |
Weijia Xu; Sweta Agrawal; Eleftheria Briakou; Marianna J. Martindale; Marine Carpuat; | arxiv-cs.CL | 2023-01-18 |
| 567 | Unsupervised Mandarin-Cantonese Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Highlight: The key contributions of our project include: 1. |
Megan Dare; Valentina Fajardo Diaz; Averie Ho Zoen So; Yifan Wang; Shibingfeng Zhang; | arxiv-cs.CL | 2023-01-10 |
| 568 | Automatic Standardization of Arabic Dialects for Machine Translation Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Carrying out this research could then lead to combining ”automatic standardization” software and automatic translation software so that we take the output of the first software and introduce it as input into the second one to obtain at the end a quality machine translation. |
Abidrabbo Alnassan; | arxiv-cs.CL | 2023-01-09 |
| 569 | Applying Automated Machine Translation to Educational Video Courses Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: We studied the capability of automated machine translation in the online video education space by automatically translating Khan Academy videos with state-of-the-art translation models and applying text-to-speech synthesis and audio/video synchronization to build engaging videos in target languages. |
Linden Wang; | arxiv-cs.CL | 2023-01-08 |
| 570 | Building A Parallel Corpus and Training Translation Models Between Luganda and English Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: In this paper, we build a parallel corpus with 41,070 pairwise sentences for Luganda and English which is based on three different open-sourced corpora. |
Richard Kimera; Daniela N. Rim; Heeyoul Choi; | arxiv-cs.CL | 2023-01-06 |
| 571 | Statistical Machine Translation for Indic Languages Related Papers Related Patents Related Grants Related Venues Related Experts View Highlight: Different preprocessing approaches are proposed in this paper to handle the noise of the dataset. |
Sudhansu Bala Das; Divyajoti Panda; Tapas Kumar Mishra; Bidyut Kr. Patra; | arxiv-cs.CL | 2023-01-02 |
| 572 | Rahul Patil at SemEval-2023 Task 1: V-WSD: Visual Word Sense Disambiguation |