Machine Translation

Also known as MT

Overview

Machine translation studies how to produce useful translations across languages, including low-resource languages, specialized domains, dialects, and long or multimodal content. Common approaches include Transformer-based neural systems and large language models, adapted with parallel or synthetic data, retrieval, preference optimization, and reinforcement learning; speech and image translation also combine language models with audio or visual information. Evaluation uses automatic metrics and human review, with newer benchmarks testing terminology, context, cultural meaning, style, bias, and instruction following. A central tension is that gains on standard scores do not always mean translations are faithful or appropriate, while broad language coverage, low latency, privacy, and limited data remain practical challenges.

Latest papers

CardsList

267 papers37 papers in the last four weeks, level with the four weeks before. 0.2% of all new papers.

  1. Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey

    Apr 13, 2026Bingzheng Qu, Kehai Chen, Xuefeng Bai +1Lip SynchronizationVideo-to-Video Translation

  2. Should We be Pedantic About Reasoning Errors in Machine Translation?

    Apr 10, 2026Calvin Bao, Marine CarpuatMachine TranslationMT Evaluation

  3. Evaluating In-Context Translation with Synchronous Context-Free Grammar Transduction

    Apr 8, 2026Jackson Petty, Jaulie Goe, Tal LinzenMachine TranslationIn-Context Learning

  4. Video-guided Machine Translation with Global Video Context

    Apr 8, 2026Jian Chen, JinZe Lv, Zi Long +1Machine TranslationCross-Modal Attention

  5. Context-Aware Dialectal Arabic Machine Translation with Interactive Region and Register Selection

    Apr 7, 2026Afroza Nowshin, Prithweeraj Acharjee Porag, Haziq Jeelani +1Machine TranslationArabic NLP

  6. One Model to Translate Them All? A Journey to Mount Doom for Multilingual Model Merging

    Apr 3, 2026Baban Gain, Trilok Nath Singh, Asif EkbalMultilingual Language ModelsLanguage Model Merging

  7. Open Machine Translation for Esperanto

    Mar 31, 2026Ona de Gibert, Lluís de GibertMachine TranslationMT Evaluation

  8. Top-down string-to-dependency Neural Machine Translation

    Mar 30, 2026Shuhei Kondo, Katsuhito Sudoh, Yuji MatsumotoMachine Translation

  9. Towards High-Quality Machine Translation for Kokborok: A Low-Resource Tibeto-Burman Language of Northeast India

    Mar 28, 2026Badal Nyalang, Biman DebbarmaMachine TranslationLow-Resource MT

  10. Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties

    Mar 26, 2026Jannis Vamvas, Ignacio Pérez Prat, Angela Heldstab +3Machine TranslationLow-Resource MT

  11. Cross-Preference Learning for Sentence-Level and Context-Aware Machine Translation

    Mar 26, 2026Ying Li, Xinglin Lyu, Junhui Li +5Context-Aware MTMachine Translation

  12. Samasāmayik: A Parallel Dataset for Hindi-Sanskrit Machine Translation

    Mar 25, 2026N J Karthika, Keerthana Suryanarayanan, Jahanvi Purohit +3Machine TranslationLow-Resource MT

  13. MMTIT-Bench: A Multilingual and Multi-Scenario Benchmark with Cognition-Perception-Reasoning Guided Text-Image Machine Translation

    Mar 25, 2026Gengluo Li, Chengquan Zhang, Yupu Liang +9Image Text TranslationMachine Translation

  14. Multilingual KokoroChat: A Multi-LLM Ensemble Translation Method for Creating a Multilingual Counseling Dialogue Dataset

    Mar 24, 2026Ryoma Suzuki, Zhiyang Qi, Michimasa InabaMachine TranslationMulti-LLM Collaboration

  15. Enhancing Document-Level Machine Translation via Filtered Synthetic Corpora and Two-Stage LLM Adaptation

    Mar 23, 2026Ireh Kim, Tesia Sker, Chanwoo KimMachine TranslationDocument-Level MT

  16. Current LLMs still cannot 'talk much' about grammar modules: Evidence from syntax

    Mar 20, 2026Mohammed Q. Shormani, Yehia A. AlSohbaniMachine Translation

  17. SAGE: Sustainable Agent-Guided Expert-tuning for Culturally Attuned Translation in Low-Resource Southeast Asia

    Mar 20, 2026Zhixiang Lu, Chong Zhang, Yulong Li +5Machine TranslationLow-Resource MT

  18. ConGA: Guidelines for Contextual Gender Annotation. A Framework for Annotating Gender in Machine Translation

    Mar 18, 2026Argentina Anna Rescigno, Eva Vanmassenhove, Johanna MontiMachine TranslationMT Evaluation

  19. Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures

    Mar 18, 2026Chiara Manna, Hosein Mohebbi, Afra Alishahi +2Gender Bias in Language ModelsLanguage Model Bias Evaluation

  20. From Words to Worlds: Benchmarking Cross-Cultural Cultural Understanding in Machine Translation

    Mar 18, 2026Bangju Han, Yingqi Wang, Huang Qing +6Cross-Cultural Language Model EvaluationMachine Translation

  21. Ensemble Self-Training for Unsupervised Machine Translation

    Mar 17, 2026Ido Aharon, Jonathan Shaki, Sarit KrausMachine Translation

  22. Can Linguistically Related Languages Guide LLM Translation in Low-Resource Settings?

    Mar 17, 2026Aishwarya Ramasethu, Niyathi Allu, Rohin Garg +2Machine TranslationLow-Resource MT

  23. Omnilingual MT: Machine Translation for 1,600 Languages

    Mar 17, 2026Omnilingual MT Team, Belen Alastruey, Niyati Bafna +29Machine TranslationLow-Resource MT

  24. Machine Translation in the Wild: User Reaction to Xiaohongshu's Built-In Translation Feature

    Mar 16, 2026Sui HeMachine Translation

  25. Bidirectional Chinese and English Passive Sentences Dataset for Machine Translation

    Mar 16, 2026Xinyue Ma, Pol Pastells, Mireia Farrús +1Machine TranslationMT Evaluation

  26. ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation

    Mar 16, 2026Yuzhe Shang, Pengzhi Gao, Yazheng Yang +4Machine TranslationDecoder-Only Language Models

  27. Developing an English-Efik Corpus and Machine Translation System for Digitization Inclusion

    Mar 16, 2026Offiong Bassey Edet, Mbuotidem Sunday Awak, Emmanuel Oyo-Ita +2Machine TranslationLow-Resource MT