Table of Contents

• Frontmatter [doi]
• Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved YetTom Kocmi, Eleftherios Avramidis, Rachel Bawden, Ondrej Bojar, Anton Dvorkovich, Christian Federmann, Mark Fishel, Markus Freitag, Thamme Gowda, Roman Grundkiewicz, Barry Haddow, Marzena Karpinska, Philipp Koehn, Benjamin Marie, Christof Monz, Kenton Murray, Masaaki Nagata, Martin Popel, Maja Popovic, Mariya Shmatova, Steinthór Steingrímsson, Vilém Zouhar. 1-46 [doi]
• Are LLMs Breaking MT Metrics? Results of the WMT24 Metrics Shared TaskMarkus Freitag, Nitika Mathur, Daniel Deutsch, Chi-kiu Lo, Eleftherios Avramidis, Ricardo Rei, Brian Thompson 0001, Frédéric Blain, Tom Kocmi, Jiayi Wang, David Ifeoluwa Adelani, Marianna Buchicchio, Chrysoula Zerva, Alon Lavie. 47-81 [doi]
• Findings of the Quality Estimation Shared Task at WMT 2024: Are LLMs Closing the Gap in QE?Chrysoula Zerva, Frédéric Blain, José Guilherme Camargo de Souza, Diptesh Kanojia, Sourabh Dattatray Deoghare, Nuno Miguel Guerreiro, Giuseppe Attanasio, Ricardo Rei, Constantin Orasan, Matteo Negri, Marco Turchi, Rajen Chatterjee, Pushpak Bhattacharyya, Markus Freitag, André Martins. 82-109 [doi]
• Findings of the WMT 2024 Shared Task of the Open Language Data InitiativeJean Maillard, Laurie Burchell, Antonios Anastasopoulos, Christian Federmann, Philipp Koehn, Skyler Wang. 110-117 [doi]
• Results of the WAT/WMT 2024 Shared Task on Patent TranslationShohei Higashiyama. 118-123 [doi]
• Findings of the WMT 2024 Biomedical Translation Shared Task: Test Sets on Abstract LevelMariana L. Neves, Cristian Grozea, Philippe Thomas 0002, Roland Roller, Rachel Bawden, Aurélie Névéol, Steffen Castle, Vanessa Bonato, Giorgio Maria Di Nunzio, Federica Vezzani, Maika Vicente Navarro, Lana Yeganova, Antonio Jimeno-Yepes. 124-138 [doi]
• MSLC24 Submissions to the General Machine Translation TaskSamuel Larkin, Chi-liu Lo, Rebecca Knowles. 139-146 [doi]
• IOL Research Machine Translation Systems for WMT24 General Machine Translation Shared TaskWenbo Zhang. 147-154 [doi]
• Choose the Final Translation from NMT and LLM Hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared TaskZhanglin Wu, Daimeng Wei, Zongyao Li, Hengchao Shang, Jiaxin Guo, Shaojun Li, Zhiqiang Rao, Yuanchang Luo, Ning Xie, Hao Yang. 155-164 [doi]
• CycleGN: A Cycle Consistent Approach for Neural Machine TranslationSören Dreano, Derek Molloy, Noel Murphy. 165-175 [doi]
• UvA-MT's Participation in the WMT24 General Translation Shared TaskShaomu Tan, David Stap, Seth Aycock, Christof Monz, Di Wu. 176-184 [doi]
• Tower v2: Unbabel-IST 2024 Submission for the General MT Shared TaskRicardo Rei, José Pombal, Nuno Miguel Guerreiro, João Alves, Pedro Henrique Martins, Patrick Fernandes, Helena Wu, Tânia Vaz, Duarte M. Alves, M. Amin Farajian, Sweta Agrawal, António Farinhas, José Guilherme Camargo de Souza, André Martins. 185-204 [doi]
• TSU HITS's Submissions to the WMT 2024 General Machine Translation Shared TaskVladimir Mynka, Nikolay Mikhaylovskiy. 205-209 [doi]
• Document-level Translation with LLM Reranking: Team-J at WMT 2024 General Translation TaskKeito Kudo, Hiroyuki Deguchi, Makoto Morishita, Ryo Fujii, Takumi Ito, Shintaro Ozaki, Koki Natsumi, Kai Sato, Kazuki Yano, Ryosuke Takahashi, Subaru Kimura, Tomomasa Hara, Yusuke Sakai 0010, Jun Suzuki 0001. 210-226 [doi]
• DLUT and GTCOM's Neural Machine Translation Systems for WMT24Hao Zong, Chao Bei, Huan Liu, Conghu Yuan, Wentao Chen, Degen Huang. 227-231 [doi]
• CUNI at WMT24 General Translation Task: LLMs, (Q)LoRA, CPO and Model MergingMiroslav Hrabal, Josef Jon, Martin Popel, Nam Luu, Danil Semin, Ondrej Bojar. 232-246 [doi]
• From General LLM to Translation: How We Dramatically Improve Translation Quality Using Human Evaluation Data for LLM FinetuningDenis Elshin, Nikolay Karpachev, Boris Gruzdev, Ilya Golovanov, Georgy Ivanov, Alexander Antonov, Nickolay Skachkov, Ekaterina Latypova, Vladimir Layner, Ekaterina Enikeeva, Dmitry Popov, Anton Chekashev, Vladislav Negodin, Vera Frantsuzova, Alexander Chernyshev, Kirill Denisov. 247-252 [doi]
• Cogs in a Machine, Doing What They're Meant to Do - the AMI Submission to the WMT24 General Translation TaskAtli Jasonarson, Hinrik Hafsteinsson, Bjarki Ármannsson, Steinthór Steingrímsson. 253-262 [doi]
• IKUN for WMT24 General MT Task: LLMs Are Here for Multilingual Machine TranslationBaohao Liao, Christian Herold, Shahram Khadivi, Christof Monz. 263-269 [doi]
• NTTSU at WMT2024 General Translation TaskMinato Kondo, Ryo Fukuda, Xiaotian Wang, Katsuki Chousa, Masato Nishimura, Kosei Buma, Takatomo Kano, Takehito Utsuro. 270-279 [doi]
• SCIR-MT's Submission for WMT24 General Machine Translation TaskBaohang Li, Zekai Ye, Yichong Huang, Xiaocheng Feng, Bing Qin 0001. 280-285 [doi]
• AIST AIRC Systems for the WMT 2024 Shared TasksMatiss Rikters, Makoto Miwa. 286-291 [doi]
• Occiglot at WMT24: European Open-source Large Language Models Evaluated on TranslationEleftherios Avramidis, Annika Grützner-Zahn, Manuel Brack, Patrick Schramowski, Pedro Ortiz Suarez, Malte Ostendorff, Fabio Barth, Shushen Manakhimova, Vivien Macketanz, Georg Rehm, Kristian Kersting. 292-298 [doi]
• CoST of breaking the LLMsAnanya Mukherjee, Saumitra Yadav, Manish Shrivastava 0001. 299-306 [doi]
• WMT24 Test Suite: Gender Resolution in Speaker-Listener Dialogue RolesHillary Dawkins, Isar Nejadgholi, Chi-kiu Lo. 307-326 [doi]
• The GenderQueer Test SuiteSteinunn Rut Friidhriksdóttir. 327-340 [doi]
• Domain Dynamics: Evaluating Large Language Models in English-Hindi TranslationSoham Bhattacharjee, Baban Gain, Asif Ekbal. 341-354 [doi]
• Investigating the Linguistic Performance of Large Language Models in Machine TranslationShushen Manakhimova, Vivien Macketanz, Eleftherios Avramidis, Ekaterina Lapshinova-Koltunski, Sergei Bagdasarov, Sebastian Möller 0001. 355-371 [doi]
• IsoChronoMeter: A Simple and Effective Isochronic Translation Evaluation MetricNikolai Rozanov, Vikentiy Pankov, Dmitrii Mukhutdinov, Dima Vypirailenko. 372-379 [doi]
• A Test Suite of Prompt Injection Attacks for LLM-based Machine TranslationAntonio Valerio Miceli Barone, Zhifan Sun. 380-450 [doi]
• Killing Two Flies with One Stone: An Attempt to Break LLMs Using English-Icelandic Idioms and Proper NamesBjarki Ármannsson, Hinrik Hafsteinsson, Atli Jasonarson, Steinthór Steingrímsson. 451-458 [doi]
• MetaMetrics-MT: Tuning Meta-Metrics for Machine Translation via Human Preference CalibrationDavid Anugraha, Garry Kuwanto, Lucky Susanto, Derry Tanti Wijaya, Genta Indra Winata. 459-469 [doi]
• chrF-S: Semantics Is All You NeedAnanya Mukherjee, Manish Shrivastava 0001. 470-474 [doi]
• MSLC24: Further Challenges for Metrics on a Wide Landscape of Translation QualityRebecca Knowles, Samuel Larkin, Chi-kiu Lo. 475-491 [doi]
• MetricX-24: The Google Submission to the WMT 2024 Metrics Shared TaskJuraj Juraska, Daniel Deutsch, Mara Finkelstein, Markus Freitag. 492-504 [doi]
• Evaluating WMT 2024 Metrics Shared Task Submissions on AfriMTE (the African Challenge Set)Jiayi Wang, David Ifeoluwa Adelani, Pontus Stenetorp. 505-516 [doi]
• Machine Translation Metrics Are Better in Evaluating Linguistic Errors on LLMs than on Encoder-Decoder SystemsEleftherios Avramidis, Shushen Manakhimova, Vivien Macketanz, Sebastian Möller 0001. 517-528 [doi]
• TMU-HIT's Submission for the WMT24 Quality Estimation Shared Task: Is GPT-4 a Good Evaluator for Machine Translation?Ayako Sato, Kyotaro Nakajima, Hwichan Kim, Zhousi Chen, Mamoru Komachi. 529-534 [doi]
• HW-TSC 2024 Submission for the Quality Estimation Shared TaskWeiqiao Shan, Ming Zhu 0010, Yuang Li, Mengyao Piao, Xiaofeng Zhao, Chang Su 0001, Min Zhang, Hao Yang 0006, Yanfei Jiang. 535-540 [doi]
• HW-TSC's Participation in the WMT 2024 QEAPE TaskJiawei Yu, Xiaofeng Zhao, Min Zhang, Yanqing Zhao, Yuang Li, Chang Su 0001, Xiaosong Qiao, Miaomiao Ma, Hao Yang 0006. 541-546 [doi]
• Expanding the FLORES+ Multilingual Benchmark with Translations for Aragonese, Aranese, Asturian, and ValencianJuan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez, Víctor M. Sánchez-Cartagena, Miquel Esplà-Gomis, Aarón Galiano Jiménez, Antoni Oliver 0001, Claudi Aventín-Boya, Alejandro Pardos, Cristina Valdés, Jusèp Loís Sans Socasau, Juan Pablo Martínez. 547-555 [doi]
• The Bangla/Bengali Seed Dataset Submission to the WMT24 Open Language Data Initiative Shared TaskFiroz Ahmed, Nitin Venkateswaran, Sarah Moeller. 556-566 [doi]
• A High-quality Seed Dataset for Italian Machine TranslationEdoardo Ferrante. 567-569 [doi]
• Correcting FLORES Evaluation Dataset for Four African LanguagesIdris Abdulmumin, Sthembiso Mkhwanazi, Mahlatse S. Mbooi, Shamsuddeen Hassan Muhammad, Ibrahim Said Ahmad, Neo Putini, Miehleketo Mathebula, Matimba Shingange, Tajuddeen Gwadabe, Vukosi Marivate. 570-578 [doi]
• Expanding FLORES+ Benchmark for More Low-Resource Settings: Portuguese-Emakhuwa Machine Translation EvaluationFelermino Dario Mario Ali, Henrique Lopes Cardoso, Rui Sousa-Silva. 579-592 [doi]
• Enhancing Tuvan Language Resources through the FLORES DatasetAli Kuzhuget, Airana Mongush, Nachyn-Enkhedorzhu Oorzhak. 593-599 [doi]
• Machine Translation Evaluation Benchmark for Wu Chinese: Workflow and AnalysisHongjian Yu, Yiming Shi, Zherui Zhou, Christopher Haberland. 600-605 [doi]
• Open Language Data Initiative: Advancing Low-Resource Machine Translation for KarakalpakMukhammadsaid Mamasaidov, Abror Shopulatov. 606-613 [doi]
• FLORES+ Translation and Machine Translation Evaluation for the Erzya LanguageIsai Gordeev, Sergey Kuldin, David Dale. 614-623 [doi]
• Spanish Corpus and Provenance with Computer-Aided Translation for the WMT24 OLDI Shared TaskJose Cols. 624-635 [doi]
• Efficient Terminology Integration for LLM-based Translation in Specialized DomainsSejoon Kim, Mingi Sung, Jeonghwan Lee, Hyunkuk Lim, Jorge Gimenez Perez. 636-642 [doi]
• Rakuten's Participation in WMT 2024 Patent Translation TaskOhnmar Htun, Alberto Poncelas. 643-646 [doi]
• The SETU-ADAPT Submission for WMT 24 Biomedical Shared TaskAntonio Castaldo, Maria Zafar, Prashanth Nayak, Rejwanul Haque, Andy Way, Johanna Monti. 647-653 [doi]
• Findings of WMT 2024 Shared Task on Low-Resource Indic Languages TranslationPartha Pakray, Santanu Pal, Advaitha Vetagiri, Reddi Krishna, Arnab Kumar Maji, Sandeep Kumar Dash, Lenin Laitonjam, Lyngdoh Sarah, Riyanka Manna. 654-668 [doi]
• Findings of WMT 2024's MultiIndic22MT Shared Task for Machine Translation of 22 Indian LanguagesRaj Dabre, Anoop Kunchukuttan. 669-676 [doi]
• Findings of WMT2024 English-to-Low Resource Multimodal Translation TaskShantipriya Parida, Ondrej Bojar, Idris Abdulmumin, Shamsuddeen Hassan Muhammad, Ibrahim Said Ahmad. 677-683 [doi]
• Findings of the WMT 2024 Shared Task Translation into Low-Resource Languages of Spain: Blending Rule-Based and Neural SystemsFelipe Sánchez-Martínez, Juan Antonio Pérez-Ortiz, Aarón Galiano Jiménez, Antoni Oliver 0001. 684-698 [doi]
• Findings of the WMT 2024 Shared Task on Discourse-Level Literary TranslationLongyue Wang, Siyou Liu, Chenyang Lyu, Wenxiang Jiao, Xing Wang 0007, Jiahao Xu, Zhaopeng Tu, Yan Gu, Weiyu Chen, Minghao Wu, Liting Zhou, Philipp Koehn, Andy Way, Yulin Yuan. 699-700 [doi]
• Findings of the WMT 2024 Shared Task on Chat TranslationWafaa Mohammed, Sweta Agrawal, M. Amin Farajian, Vera Cabarrão, Bryan Eikema, Ana C. Farinha, José Guilherme Camargo de Souza. 701-714 [doi]
• Findings of the WMT 2024 Shared Task on Non-Repetitive TranslationKazutaka Kinugawa, Hideya Mino, Isao Goto, Naoto Shirai. 715-727 [doi]
• A3-108 Controlling Token Generation in Low Resource Machine Translation SystemsSaumitra Yadav, Ananya Mukherjee, Manish Shrivastava 0001. 728-734 [doi]
• Samsung R&D Institute Philippines @ WMT 2024 Indic MT TaskMatthew Theodore Roque, Carlos Rafael Catalan, Dan John Velasco, Manuel Antonio Rufino, Jan Christian Blaise Cruz. 735-741 [doi]
• DLUT-NLP Machine Translation Systems for WMT24 Low-Resource Indic Language TranslationChenfei Ju, Junpeng Liu, Kaiyu Huang, Degen Huang. 742-746 [doi]
• SRIB-NMT's Submission to the Indic MT Shared Task in WMT 2024Pranamya Patil, Raghavendra Hr, Aditya Raghuwanshi, Kushal Verma. 747-750 [doi]
• MTNLP-IIITH: Machine Translation for Low-Resource Indic LanguagesAbhinav P. M, Ketaki Shetye, Parameswari Krishnamurthy. 751-755 [doi]
• Exploration of the CycleGN Framework for Low-Resource LanguagesSören Dreano, Derek Molloy, Noel Murphy. 756-761 [doi]
• The SETU-ADAPT Submissions to the WMT24 Low-Resource Indic Language Translation TaskNeha Gajakos, Prashanth Nayak, Rejwanul Haque, Andy Way. 762-769 [doi]
• SPRING Lab IITM's Submission to Low Resource Indic Language Translation Shared TaskAdvait Joglekar, Hamees Ul Hasan Sayed, Srinivasan Umesh. 770-774 [doi]
• Machine Translation Advancements of Low-Resource Indian Languages by Transfer LearningBin Wei, Jiawei Zheng, Zongyao Li, Zhanglin Wu, Jiaxin Guo, Daimeng Wei, Zhiqiang Rao, Shaojun Li, Yuanchang Luo, Hengchao Shang, Jinlong Yang, Yuhao Xie, Hao Yang. 775-780 [doi]
• NLIP_Lab-IITH Low-Resource MT System for WMT24 Indic MT Shared TaskPramit Sahoo, Maharaj Brahma, Maunendra Sankar Desarkar. 781-787 [doi]
• Yes-MT's Submission to the Low-Resource Indic Language Translation Shared Task in WMT 2024Yash Bhaskar, Parameswari Krishnamurthy. 788-792 [doi]
• System Description of BV-SLP for Sindhi-English Machine Translation in MultiIndic22MT 2024 Shared TaskNisheeth Joshi, Pragya Katyayan, Palak Arora, Bharti Nathani. 793-796 [doi]
• WMT24 System Description for the MultiIndic22MT Shared Task on Manipuri LanguageNingthoujam Justwant Singh, Kshetrimayum Boynao Singh, Avichandra Singh Ningthoujam, Sanjita Phijam, Thoudam Doren Singh. 797-803 [doi]
• NLIP-Lab-IITH Multilingual MT System for WAT24 MT Shared TaskMaharaj Brahma, Pramit Sahoo, Maunendra Sankar Desarkar. 804-809 [doi]
• DCU ADAPT at WMT24: English to Low-resource Multi-Modal Translation TaskSami Haq, Rudali Huidrom, Sheila Castilho. 810-814 [doi]
• English-to-Low-Resource Translation: A Multimodal Approach for Hindi, Malayalam, Bengali, and HausaAli Hatami, Shubhanker Banerjee, Mihael Arcan, Bharathi Raja Chakravarthi, Paul Buitelaar, John P. McCrae. 815-822 [doi]
• OdiaGenAI's Participation in WMT2024 English-to-Low Resource Multimodal Translation TaskShantipriya Parida, Shashikanta Sahoo, Sambit Sekhar, Upendra Jena, Sushovan Jena, Kusum Lata 0005. 823-828 [doi]
• Arewa NLP's Participation at WMT24Mahmoud Ahmad, Auwal Abubakar Khalid, Lukman Jibril Aliyu, Babangida Sani, Mariya Abdullahi. 829-832 [doi]
• Multimodal Machine Translation for Low-Resource Indic Languages: A Chain-of-Thought Approach Using Large Language ModelsPawan Rajpoot, Nagaraj Bhat, Ashish Shrivastava. 833-838 [doi]
• Chitranuvad: Adapting Multi-lingual LLMs for Multimodal TranslationShaharukh Khan, Ayush Tarun, Ali Faraz, Palash Kamble, Vivek Dahiya, Praveen Pokala, Ashish Kulkarni, Chandra Khatri, Abhinav Ravi, Shubham Agarwal. 839-851 [doi]
• Brotherhood at WMT 2024: Leveraging LLM-Generated Contextual Conversations for Cross-Lingual Image CaptioningSiddharth Betala, Ishan Chokshi. 852-861 [doi]
• TIM-UNIGE Translation into Low-Resource Languages of Spain for WMT24Jonathan Mutal, Lucia Ormaechea Grijalba. 862-870 [doi]
• TAN-IBE Participation in the Shared Task: Translation into Low-Resource Languages of SpainAntoni Oliver 0001. 871-877 [doi]
• Enhaced Apertium System: Translation into Low-Resource Languages of Spain Spanish-AsturianSofía García. 878-884 [doi]
• Universitat d'Alacant's Submission to the WMT 2024 Shared Task on Translation into Low-Resource Languages of SpainAarón Galiano Jiménez, Víctor M. Sánchez-Cartagena, Juan Antonio Pérez-Ortiz, Felipe Sánchez-Martínez. 885-891 [doi]
• Samsung R&D Institute Philippines @ WMT 2024 Low-resource Languages of Spain Shared TaskDan John Velasco, Manuel Antonio Rufino, Jan Christian Blaise Cruz. 892-900 [doi]
• Back to the Stats: Rescuing Low Resource Neural Machine Translation with Statistical MethodsMenan Velayuthan, Dilith Jayakody, Nisansa de Silva, Aloka Fernando, Surangika Ranathunga. 901-907 [doi]
• Hybrid Distillation from RBMT and NMT: Helsinki-NLP's Submission to the Shared Task on Translation into Low-Resource Languages of SpainOna de Gibert, Mikko Aulamo, Yves Scherrer, Jörg Tiedemann. 908-917 [doi]
• Robustness of Fine-Tuned LLMs for Machine Translation with Varying Noise Levels: Insights for Asturian, Aragonese and AraneseMartin Bär, Elisa Forcada Rodríguez, Maria Garcia-Abadillo. 918-924 [doi]
• Training and Fine-Tuning NMT Models for Low-Resource Languages Using Apertium-Based Synthetic CorporaAleix Sant, Daniel Bardanca, José Ramom Pichel Campos, Francesca de Luca Fornaciari, Carlos Escolano, Javier García Gilabert, Pablo Gamallo 0001, Audrey Mash, Xixian Liao, Maite Melero. 925-933 [doi]
• Vicomtech@WMT 2024: Shared Task on Translation into Low-Resource Languages of SpainDavid Ponce, Harritxu Gete, Thierry Etchegoyhen. 934-942 [doi]
• SJTU System Description for the WMT24 Low-Resource Languages of Spain TaskTianxiang Hu, Haoxiang Sun, Ruize Gao, Jialong Tang, Pei Zhang 0011, Baosong Yang, Rui Wang 0015. 943-948 [doi]
• Multilingual Transfer and Domain Adaptation for Low-Resource Languages of SpainYuanchang Luo, Zhanglin Wu, Daimeng Wei, Hengchao Shang, Zongyao Li, Jiaxin Guo, Zhiqiang Rao, Shaojun Li, Jinlong Yang, Yuhao Xie, Jiawei Zheng, Bin Wei, Hao Yang. 949-954 [doi]
• TRIBBLE - TRanslating IBerian languages Based on Limited E-resourcesIgor Kuzmin, Piotr Przybyla, Euan McGill, Horacio Saggion. 955-959 [doi]
• CloudSheep System for WMT24 Discourse-Level Literary TranslationLisa Liu, Ryan Liu, Angela Tsai, Jingbo Shang. 960-966 [doi]
• Final Submission of SJTULoveFiction to Literary TaskHaoxiang Sun, Tianxiang Hu, Ruize Gao, Jialong Tang, Pei Zhang 0011, Baosong Yang, Rui Wang 0015. 967-972 [doi]
• Context-aware and Style-related Incremental Decoding Framework for Discourse-Level Literary TranslationYuanchang Luo, Jiaxin Guo, Daimeng Wei, Hengchao Shang, Zongyao Li, Zhanglin Wu, Zhiqiang Rao, Shaojun Li, Jinlong Yang, Hao Yang. 973-979 [doi]
• NovelTrans: System for WMT24 Discourse-Level Literary TranslationYuchen Liu, Yutong Yao, Runzhe Zhan, Yuchu Lin, Derek F. Wong. 980-986 [doi]
• LinChance-NTU for Unconstrained WMT2024 Literary TranslationKechen Li, Yaotian Tao, Hongyi Huang, Tianbo Ji. 987-992 [doi]
• Improving Context Usage for Translating Bilingual Customer Support Chat with Large Language ModelsJosé Pombal, Sweta Agrawal, André Martins. 993-1003 [doi]
• Optimising LLM-Driven Machine Translation with Context-Aware Sliding WindowsXinye Yang, Yida Mu, Kalina Bontcheva, Xingyi Song. 1004-1010 [doi]
• Context-Aware LLM Translation System Using Conversation Summarization and Dialogue HistoryMingi Sung, Seungmin Lee, Jiwon Kim, Sejoon Kim. 1011-1015 [doi]
• Enhancing Translation Quality: A Comparative Study of Fine-Tuning and Prompt Engineering in Dialog-Oriented Machine Translation Systems. Insights from the MULTITAN-GML TeamLichao Zhu, Maria Zimina, Behnoosh Namdarzadeh, Nicolas Ballier, Jean-Baptiste Yunès. 1016-1022 [doi]
• The SETU-ADAPT Submissions to WMT 2024 Chat Translation TasksMaria Zafar, Antonio Castaldo, Prashanth Nayak, Rejwanul Haque, Andy Way. 1023-1030 [doi]
• Exploring the Traditional NMT Model and Large Language Model for Chat TranslationJinlong Yang, Hengchao Shang, Daimeng Wei, Jiaxin Guo, Zongyao Li, Zhanglin Wu, Zhiqiang Rao, Shaojun Li, Yuhao Xie, Yuanchang Luo, Jiawei Zheng, Bin Wei, Hao Yang 0006. 1031-1037 [doi]
• Graph Representations for Machine Translation in Dialogue SettingsLea Krause, Selene Baez Santamaría, Jan-Christoph Kalo. 1038-1046 [doi]
• Reducing Redundancy in Japanese-to-English Translation: A Multi-Pipeline Approach for Translating Repeated Elements in JapaneseQiao Wang, Yixuan Huang, Zheng Yuan. 1047-1055 [doi]
• SYSTRAN @ WMT24 Non-Repetitive Translation TaskMarko Avila, Josep Crego. 1056-1062 [doi]
• Mitigating Metric Bias in Minimum Bayes Risk DecodingGeza Kovacs, Daniel Deutsch, Markus Freitag. 1063-1094 [doi]
• Beyond Human-Only: Evaluating Human-Machine Collaboration for Collecting High-Quality Translation DataZhongtao Liu, Parker Riley, Daniel Deutsch, Alison Lui, Mengmeng Niu, Apurva Shah, Markus Freitag. 1095-1106 [doi]
• How Effective Are State Space Models for Machine Translation?Hugo Pitorro, Pavlo Vasylenko, Marcos V. Treviso, André Martins. 1107-1124 [doi]
• Evaluation and Large-scale Training for Contextual Machine TranslationMatt Post, Marcin Junczys-Dowmunt. 1125-1139 [doi]
• A Multi-task Learning Framework for Evaluating Machine Translation of Emotion-loaded User-generated ContentShenbin Qian, Constantin Orasan, Diptesh Kanojia, Félix do Carmo. 1140-1154 [doi]
• On Instruction-Finetuning Neural Machine Translation ModelsVikas Raunak, Roman Grundkiewicz, Marcin Junczys-Dowmunt. 1155-1166 [doi]
• Benchmarking Visually-Situated Translation of Text in Natural ImagesElizabeth Salesky, Philipp Koehn, Matt Post. 1167-1182 [doi]
• Analysing Translation Artifacts: A Comparative Study of LLMs, NMTs, and Human TranslationsFedor Sizov, Cristina España-Bonet, Josef van Genabith, Roy Xie, Koel Dutta Chowdhury. 1183-1199 [doi]
• How Grammatical Features Impact Machine Translation: A New Test Suite for Chinese-English MT EvaluationHuacheng Song, Yi Li, Yiwen Wu, Yu Liu, Jingxia Lin, Hongzhi Xu. 1200-1221 [doi]
• Improving Statistical Significance in Human Evaluation of Automatic Metrics via Soft Pairwise AccuracyBrian Thompson 0001, Nitika Mathur, Daniel Deutsch, Huda Khayrallah. 1222-1234 [doi]
• Speech Is More than Words: Do Speech-to-Text Translation Systems Leverage Prosody?Ioannis Tsiamas, Matthias Sperber, Andrew Finch, Sarthak Garg. 1235-1257 [doi]
• Cultural Adaptation of Menus: A Fine-Grained ApproachZhonghe Zhang, Xiaoyu He, Vivek Iyer, Alexandra Birch. 1258-1271 [doi]
• Pitfalls and Outlooks in Using COMETVilém Zouhar, Pinzhen Chen, Tsz Kin Lam, Nikita Moghe, Barry Haddow. 1272-1288 [doi]
• Post-edits Are Preferences TooNathaniel Berger, Stefan Riezler, Miriam Exel, Matthias Huck. 1289-1300 [doi]
• Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form TextsEleftheria Briakou, Jiaming Luo, Colin Cherry, Markus Freitag. 1301-1317 [doi]
• Scaling Laws of Decoder-Only Models on the Multilingual Machine Translation TaskGaëtan Caillaut, Mariam Nakhlé, Raheel Qader, Jingshu Liu, Jean-Gabriel Barthelemy. 1318-1331 [doi]
• Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding Are Both the ProblemSara Court, Micha Elsner. 1332-1354 [doi]
• Introducing the NewsPaLM MBR and QE Dataset: LLM-Generated High-Quality Parallel Data Outperforms Traditional Web-Crawled DataMara Finkelstein, David Vilar, Markus Freitag. 1355-1372 [doi]
• Is Preference Alignment Always the Best Option to Enhance LLM-Based Translation? An Empirical AnalysisHippolyte Gisserot-Boukhlef, Ricardo Rei, Emmanuel Malherbe, Céline Hudelot, Pierre Colombo, Nuno Miguel Guerreiro. 1373-1392 [doi]
• Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource TranslationVivek Iyer, Bhavitvya Malik, Pavel Stepachev, Pinzhen Chen, Barry Haddow, Alexandra Birch. 1393-1409 [doi]
• Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology TranslationJiyoon Myung, Jihyeon Park, Jungki Son, Kyungro Lee, Joohyung Han. 1410-1427 [doi]
• Assessing the Role of Imagery in Multimodal Machine TranslationNicholas Kashani Motlagh, Jim Davis, Jeremy Gwinnup, Grant Erdmann, Tim Anderson. 1428-1439 [doi]
• Error Span Annotation: A Balanced Approach for Human Evaluation of Machine TranslationTom Kocmi, Vilém Zouhar, Eleftherios Avramidis, Roman Grundkiewicz, Marzena Karpinska, Maja Popovic, Mrinmaya Sachan, Mariya Shmatova. 1440-1453 [doi]
• Neural Methods for Aligning Large-Scale Parallel Corpora from the Web for South and East Asian LanguagesPhilipp Koehn. 1454-1466 [doi]
• Plug, Play, and Fuse: Zero-Shot Joint Decoding via Word-Level Re-ranking across Diverse VocabulariesSai Koneru, Matthias Huck, Miriam Exel, Jan Niehues. 1467-1481 [doi]