mlsanityData to 7 Oct 2026

Document-Level Machine Translation with Large Language Models

arXiv 2304.02210 ↗First posted 5 Apr 2023cs.CL cs.AIcited by 90

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Abstract (arXiv)

Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level machine translation (MT) as a testbed, this paper provides an in-depth evaluation of LLMs' ability on discourse modeling. 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. By evaluating on a number of benchmarks, we surprisingly find that LLMs have demonstrated superior performance and show potential to become a new paradigm for document-level translation: 1) leveraging their powerful long-text modeling capabilities, GPT-3.5 and GPT-4 outperform commercial MT systems in terms of human evaluation; 2) GPT-4 demonstrates a stronger ability for probing linguistic knowledge than GPT-3.5. This work highlights the challenges and opportunities of LLMs for MT, which we hope can inspire the future design and evaluation of LLMs.We release our data and annotations at https://github.com/longyuewangdcu/Document-MT-LLM.

Key facts. Cited by 90 papers in the map (data through 7 Oct 2026). Builds on 30 of its 56 references that are in the map. First posted on arXiv 5 Apr 2023.

Builds on

30 of 56 references.

References · 30

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  5. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  6. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,813
  7. 2018A Call for Clarity in Reporting BLEU Scorescited by 1,790
  8. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,028
  9. 2020COMET: A Neural Framework for MT Evaluationcited by 1,024
  10. 2023Large Language Models Are State-of-the-Art Evaluators of Translation Qualitycited by 416
  11. 2023How Good Are GPT Models at Machine Translation? A Comprehensive Evaluationcited by 344
  12. 2020With Little Power Comes Great Responsibilitycited by 138
18 more
  1. 2018Context-Aware Neural Machine Translation Learns Anaphora Resolutioncited by 97
  2. 2017Evaluating Discourse Phenomena in Neural Machine Translationcited by 87
  3. 2023Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translationcited by 74
  4. 2017Exploiting Cross-Sentence Context for Neural Machine Translationcited by 48
  5. 2021G-Transformer for Document-level Machine Translationcited by 46
  6. 2022Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literaturecited by 45
  7. 2019Context-Aware Monolingual Repair for Neural Machine Translationcited by 41
  8. 2017Learning to Remember Translation History with a Continuous Cachecited by 39
  9. 2020Incorporating BERT into Parallel Sequence Decoding with Adapterscited by 39
  10. 2020Rethinking Document-level Neural Machine Translationcited by 32
  11. 2021TranSmart: A Practical Interactive Machine Translation Systemcited by 17
  12. 2018Translating Pro-Drop Languages with Reconstruction Modelscited by 14
  13. 2019One Model to Learn Both: Zero Pronoun Prediction and Translationcited by 14
  14. 2016A Novel Approach to Dropped Pronoun Translationcited by 9
  15. 2019Using Whole Document Context in Neural Machine Translationcited by 9
  16. 2020Towards Making the Most of Context in Neural Machine Translationcited by 7
  17. 2021Multilingual Document-Level Translation Enables Zero-Shot Transfer From Sentences to Documentscited by 7
  18. 2018Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanismcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 23; 2024: 36; 2025: 28; 2026: 3.

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  1. 2024LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Modelscited by 1,442
  2. 2023A Survey on Evaluation of Large Language Modelscited by 1,227
  3. 2023Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integrationcited by 168
  4. 2023A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethicscited by 162
  5. 2023Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Surveycited by 134
  6. 2024Large Language Models Meet NLP: A Surveycited by 102
  7. 2025AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progresscited by 69
  8. 2024MarsCode Agent: AI-native Automated Bug Fixingcited by 68
  9. 2023BigTranslate: Augmenting Large Language Models with Multilingual Translation Capability over 100 Languagescited by 60
  10. 2024Adapting Large Language Models for Document-Level Machine Translationcited by 59
  11. 2023TrustGPT: A Benchmark for Trustworthy and Responsible Large Language Modelscited by 56
  12. 2023KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Basescited by 52
38 more
  1. 2024(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Textscited by 49
  2. 2023Exploring Human-Like Translation Strategy with Large Language Modelscited by 44
  3. 2024Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologiescited by 44
  4. 2023What's the Magic Word? A Control Theory of LLM Promptingcited by 41
  5. 2024Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Mediacited by 35
  6. 2023A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Timecited by 30
  7. 2023Speech Translation with Large Language Models: An Industrial Practicecited by 28
  8. 2023Escaping the sentence-level paradigm in machine translationcited by 27
  9. 2024DelTA: An Online Document-Level Translation Agent Based on Multi-Level Memorycited by 27
  10. 2023Beyond Static Datasets: A Deep Interaction Approach to LLM Evaluationcited by 24
  11. 2023ChatGPT MT: Competitive for High- (but not Low-) Resource Languagescited by 23
  12. 2024Reassessing Layer Pruning in LLMs: New Insights and Methodscited by 23
  13. 2024A Philosophical Introduction to Language Models -- Part I: Continuity With Classic Debatescited by 22
  14. 2024The Price of Prompting: Profiling Energy Use in Large Language Models Inferencecited by 22
  15. 2023Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generationcited by 21
  16. 2024Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challengescited by 18
  17. 2025Benchmarking Vision-Language Models on Chinese Ancient Documents: From OCR to Knowledge Reasoningcited by 18
  18. 2024Salute the Classic: Revisiting Challenges of Machine Translation in the Age of Large Language Modelscited by 17
  19. 2025New Trends for Modern Machine Translation with Large Reasoning Modelscited by 17
  20. 2023TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varietiescited by 16
  21. 2024Towards Achieving Human Parity on End-to-end Simultaneous Speech Translation via LLM Agentcited by 14
  22. 2024Enhancing Document-level Translation of Large Language Model via Translation Mixed-instructionscited by 13
  23. 2024Large Language Models as Code Executors: An Exploratory Studycited by 12
  24. 2025AFRIDOC-MT: Document-level MT Corpus for African Languagescited by 11
  25. 2025Multilingual Contextualization of Large Language Models for Document-Level Machine Translationcited by 11
  26. 2023Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modellingcited by 10
  27. 2023A Survey on Zero Pronoun Translationcited by 9
  28. 2024Improving Black-box Robustness with In-Context Rewritingcited by 8
  29. 2025Science Across Languages: Assessing LLM Multilingual Translation of Scientific Paperscited by 8
  30. 2025Bridging the Linguistic Divide: A Survey on Leveraging Large Language Models for Machine Translationcited by 8
  31. 2025All You Need is One: Capsule Prompt Tuning with a Single Vectorcited by 8
  32. 2023Unreflected Acceptance -- Investigating the Negative Consequences of ChatGPT-Assisted Problem Solving in Physics Educationcited by 7
  33. 2024Large Language Models "Ad Referendum": How Good Are They at Machine Translation in the Legal Domain?cited by 7
  34. 2025Source-primed Multi-turn Conversation Helps Large Language Models Translate Documentscited by 7
  35. 2025Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAGcited by 7
  36. 2024MageBench: Bridging Large Multimodal Models to Agentscited by 6
  37. 2024LLeMpower: Understanding Disparities in the Control and Access of Large Language Modelscited by 5
  38. 2024How Effective are State Space Models for Machine Translation?cited by 5

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