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# Who cites «Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation» · page 2

395 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/freitag-2021-experts-errors-context-large-scale/)

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1. [M-MAD: Multidimensional Multi-Agent Debate for Advanced Machine Translation Evaluation](https://aclanthology.org/2025.acl-long.351/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [MAATS: A Multi-Agent Automated Translation System Based on MQM Evaluation](https://arxiv.org/abs/2505.14848) *— 2025 · arXiv:2505.14848*
3. [MAS-LitEval : Multi-Agent System for Literary Translation Quality Assessment](https://arxiv.org/abs/2506.14199) *— 2025 · arXiv:2506.14199*
4. [MQM-APE: Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators](https://aclanthology.org/2025.coling-main.374/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
5. [MQM-Chat: Multidimensional Quality Metrics for Chat Translation](https://aclanthology.org/2025.coling-main.221/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
6. [MQM-MSC: Enhancing Translation Quality Estimation Interpretability with Mask-Driven Self-Correction in Large Language Models](https://aclanthology.org/2025.ccl-1.67/) *— 2025 · Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)*
7. [MT-R1-Zero: Advancing LLM-based Machine Translation via R1-Zero-like Reinforcement Learning](https://aclanthology.org/2025.findings-emnlp.1015/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
8. [MT-RewardTree: A Comprehensive Framework for Advancing LLM-Based Machine Translation via Reward Modeling](https://aclanthology.org/2025.findings-emnlp.1007/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
9. [Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets](https://aclanthology.org/2025.cl-1.4/) *— 2025 · Computational Linguistics*
10. [MetricX-25 and GemSpanEval: Google Translate Submissions to the WMT25 Evaluation Shared Task](https://aclanthology.org/2025.wmt-1.70/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
11. [Minimum Bayes Risk Decoding for Error Span Detection in Reference-Free Automatic Machine Translation Evaluation](https://arxiv.org/abs/2512.07540) *— 2025 · arXiv:2512.07540*
12. [Non-Linear Scoring Model for Translation Quality Evaluation](https://arxiv.org/abs/2511.13467) *— 2025 · arXiv:2511.13467*
13. [Nvidia-Nemo's WMT 2025 Metrics Shared Task Submission](https://aclanthology.org/2025.wmt-1.66/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
14. [OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs](https://aclanthology.org/2025.inlg-main.19/) *— 2025 · Proceedings of the 18th International Natural Language Generation Conference*
15. [Penalizing Length: Uncovering Systematic Bias in Quality Estimation Metrics](https://arxiv.org/abs/2510.22028) *— 2025 · arXiv:2510.22028*
16. [PromptOptMe: Error-Aware Prompt Compression for LLM-based MT Evaluation Metrics](https://aclanthology.org/2025.naacl-long.592/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
17. [QE4PE: Word-level Quality Estimation for Human Post-Editing](https://aclanthology.org/2025.tacl-1.64/) *— 2025 · Transactions of the Association for Computational Linguistics*
18. [Quality Estimation Reranking for Document-Level Translation](https://arxiv.org/abs/2510.08870) *— 2025 · arXiv:2510.08870*
19. [Quality-Aware Decoding: Unifying Quality Estimation and Decoding](https://aclanthology.org/2025.iwslt-1.3/) *— 2025 · Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025)*
20. [ReMedy: Learning Machine Translation Evaluation from Human Preferences with Reward Modeling](https://aclanthology.org/2025.emnlp-main.217/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
21. [Reasoning for Translation: Comparative Analysis of Chain-of-Thought and Tree-of-Thought Prompting for LLM Translation](https://aclanthology.org/2025.acl-srw.17/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
22. [Refined Assessment for Translation Evaluation: Rethinking Machine Translation Evaluation in the Era of Human-Level Systems](https://aclanthology.org/2025.findings-emnlp.1203/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
23. [Specification-Aware Machine Translation and Evaluation for Purpose Alignment](https://aclanthology.org/2025.wmt-1.7/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
24. [TEaR: Improving LLM-based Machine Translation with Systematic Self-Refinement](https://aclanthology.org/2025.findings-naacl.218/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
25. [Tagged Span Annotation for Detecting Translation Errors in Reasoning LLMs](https://aclanthology.org/2025.wmt-1.62/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
26. [Testing LLMs'' Capabilities in Annotating Translations Based on an Error Typology Designed for LSP Translation: First Experiments with ChatGPT](https://aclanthology.org/2025.mtsummit-1.15/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
27. [Towards Inducing Long-Context Abilities in Multilingual Neural Machine Translation Models](https://aclanthology.org/2025.naacl-long.366/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
28. [Translation Analytics for Freelancers: I. Introduction, Data Preparation, Baseline Evaluations](https://aclanthology.org/2025.mtsummit-1.42/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
29. [Unsupervised Word-level Quality Estimation for Machine Translation Through the Lens of Annotators (Dis)agreement](https://aclanthology.org/2025.emnlp-main.924/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
30. [Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation](https://aclanthology.org/2025.acl-long.149/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
31. [WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects](https://aclanthology.org/2025.findings-acl.634/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
32. [A Deep Analysis of the Impact of Multiword Expressions and Named Entities on Chinese-English Machine Translations](https://aclanthology.org/2024.findings-emnlp.357/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
33. [A Human Perspective on GPT-4 Translations: Analysing Faroese to English News and Blog Text Translations](https://aclanthology.org/2024.eamt-1.7/) *— 2024 · Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)*
34. [A Multi-task Learning Framework for Evaluating Machine Translation of Emotion-loaded User-generated Content](https://aclanthology.org/2024.wmt-1.113/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*
35. [AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages](https://aclanthology.org/2024.naacl-long.334/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
36. [Analysis of the Annotations from a Crowd MT Evaluation Initiative: Case Study for the Spanish-Basque Pair](https://aclanthology.org/2024.eamt-1.44/) *— 2024 · Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)*
37. [Are Large Language Models State-of-the-art Quality Estimators for Machine Translation of User-generated Content?](https://aclanthology.org/2024.wat-1.4/) *— 2024 · Proceedings of the Eleventh Workshop on Asian Translation (WAT 2024)*
38. [Barriers to Effective Evaluation of Simultaneous Interpretation](https://aclanthology.org/2024.findings-eacl.15/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
39. [Benchmarking GPT-4 against Human Translators: A Comprehensive Evaluation Across Languages, Domains, and Expertise Levels](https://arxiv.org/abs/2411.13775) *— 2024 · arXiv:2411.13775*
40. [Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics](https://md.mova.elamur.ai/free/en/docs/papers/perrella-2024-beyond-correlation-interpretable-evaluation-machine/) *— our card · 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
41. [Beyond Reference: Evaluating High Quality Translations Better than Human References](https://aclanthology.org/2024.emnlp-main.294/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
42. [COMET for Low-Resource Machine Translation Evaluation: A Case Study of English-Maltese and Spanish-Basque](https://aclanthology.org/2024.lrec-main.315/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
43. [Can Automatic Metrics Assess High-Quality Translations?](https://aclanthology.org/2024.emnlp-main.802/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
44. [ConSiDERS-The-Human Evaluation Framework: Rethinking Human Evaluation for Generative Large Language Models](https://aclanthology.org/2024.acl-long.63/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [Creative and Context-Aware Translation of East Asian Idioms with GPT-4](https://aclanthology.org/2024.findings-emnlp.544/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
46. [Critical Learning Periods: Leveraging Early Training Dynamics for Efficient Data Pruning](https://aclanthology.org/2024.findings-acl.560/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
47. [Don't Rank, Combine! Combining Machine Translation Hypotheses Using Quality Estimation](https://aclanthology.org/2024.acl-long.653/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [Enhancing Neural Machine Translation of Low-Resource Languages: Corpus Development, Human Evaluation and Explainable AI Architectures](https://arxiv.org/abs/2403.01580) *— 2024 · arXiv:2403.01580*
49. [Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models](https://aclanthology.org/2024.findings-acl.520/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
50. [Error Span Annotation: A Balanced Approach for Human Evaluation of Machine Translation](https://aclanthology.org/2024.wmt-1.131/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*
51. [Evading Data Contamination Detection for Language Models is (too) Easy](https://arxiv.org/abs/2402.02823) *— 2024 · arXiv:2402.02823*
52. [Exploring Human-Like Translation Strategy with Large Language Models](https://aclanthology.org/2024.tacl-1.13/) *— 2024 · Transactions of the Association for Computational Linguistics*
53. [FINDINGS OF THE IWSLT 2024 EVALUATION CAMPAIGN](https://aclanthology.org/2024.iwslt-1.1/) *— 2024 · Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024)*
54. [Finding Replicable Human Evaluations via Stable Ranking Probability](https://aclanthology.org/2024.naacl-long.275/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
55. [Fine-Tuned Machine Translation Metrics Struggle in Unseen Domains](https://aclanthology.org/2024.acl-short.45/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
56. [First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models](https://aclanthology.org/2024.naacl-long.128/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
57. [Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation](https://aclanthology.org/2024.emnlp-main.949/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
58. [GPT-4 vs. Human Translators: A Comprehensive Evaluation of Translation Quality Across Languages, Domains, and Expertise Levels](https://arxiv.org/abs/2407.03658) *— 2024 · arXiv:2407.03658*
59. [Guardians of the Machine Translation Meta-Evaluation: Sentinel Metrics Fall In!](https://aclanthology.org/2024.acl-long.856/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [Guiding Large Language Models to Post-Edit Machine Translation with Error Annotations](https://aclanthology.org/2024.findings-naacl.265/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
61. [How Good is Zero-Shot MT Evaluation for Low Resource Indian Languages?](https://aclanthology.org/2024.acl-short.58/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
62. [Improving Minimum Bayes Risk Decoding with Multi-Prompt](https://aclanthology.org/2024.emnlp-main.1255/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
63. [Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case Study](https://aclanthology.org/2024.sigul-1.20/) *— 2024 · Proceedings of the 3rd Annual Meeting of the Special Interest Group on Under-resourced Languages @ LREC-COLING 2024*
64. [LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback](https://aclanthology.org/2024.findings-naacl.92/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
65. [LLMs and Translation: different approaches to localization between Brazilian Portuguese and European Portuguese](https://aclanthology.org/2024.propor-1.5/) *— 2024 · Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1*
66. [LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks](https://arxiv.org/abs/2406.18403) *— 2024 · arXiv:2406.18403*
67. [LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods](https://arxiv.org/abs/2412.05579) *— 2024 · arXiv:2412.05579*
68. [Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level](https://aclanthology.org/2024.emnlp-main.860/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
69. [Learning from others'' mistakes: Finetuning machine translation models with span-level error annotations](https://arxiv.org/abs/2410.16509) *— 2024 · arXiv:2410.16509*
70. [Lessons from the Trenches on Reproducible Evaluation of Language Models](https://arxiv.org/abs/2405.14782) *— 2024 · arXiv:2405.14782*
71. [Leveraging Large Language Models for NLG Evaluation: Advances and Challenges](https://aclanthology.org/2024.emnlp-main.896/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
72. [Likelihood-based Mitigation of Evaluation Bias in Large Language Models](https://aclanthology.org/2024.findings-acl.193/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
73. [Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation](https://aclanthology.org/2024.findings-acl.211/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
74. [MT-Ranker: Reference-free machine translation evaluation by inter-system ranking](https://arxiv.org/abs/2401.17099) *— 2024 · arXiv:2401.17099*
75. [MTUncertainty: Assessing the Need for Post-editing of Machine Translation Outputs by Fine-tuning OpenAI LLMs](https://aclanthology.org/2024.eamt-1.29/) *— 2024 · Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)*
76. [Measuring Uncertainty in Neural Machine Translation with Similarity-Sensitive Entropy](https://aclanthology.org/2024.eacl-long.129/) *— 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
77. [MetricX-24: The Google Submission to the WMT 2024 Metrics Shared Task](https://aclanthology.org/2024.wmt-1.35/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*
78. [Mitigating Metric Bias in Minimum Bayes Risk Decoding](https://aclanthology.org/2024.wmt-1.109/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*
79. [Multi-Dimensional Machine Translation Evaluation: Model Evaluation and Resource for Korean](https://aclanthology.org/2024.lrec-main.1024/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
80. [NEO-BENCH: Evaluating Robustness of Large Language Models with Neologisms](https://aclanthology.org/2024.acl-long.749/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
81. [Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies](https://aclanthology.org/2024.acl-long.110/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
82. [Neuron Specialization: Leveraging Intrinsic Task Modularity for Multilingual Machine Translation](https://aclanthology.org/2024.emnlp-main.374/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
83. [On the Implications of Verbose LLM Outputs: A Case Study in Translation Evaluation](https://arxiv.org/abs/2410.00863) *— 2024 · arXiv:2410.00863*
84. [POMP: Probability-driven Meta-graph Prompter for LLMs in Low-resource Unsupervised Neural Machine Translation](https://aclanthology.org/2024.acl-long.537/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
85. [Pre-task perceptions of MT influence quality and productivity: the importance of better translator-computer interactions and implications for training](https://aclanthology.org/2024.eamt-1.37/) *— 2024 · Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)*
86. [Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement](https://aclanthology.org/2024.acl-long.826/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
87. [Quality and Quantity of Machine Translation References for Automatic Metrics](https://aclanthology.org/2024.humeval-1.1/) *— 2024 · Proceedings of the Fourth Workshop on Human Evaluation of NLP Systems (HumEval) @ LREC-COLING 2024*
88. [Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model](https://aclanthology.org/2024.acl-long.836/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
89. [Rewarding What Matters: Step-by-Step Reinforcement Learning for Task-Oriented Dialogue](https://aclanthology.org/2024.findings-emnlp.472/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
90. [Simpson's Paradox and the Accuracy-Fluency Tradeoff in Translation](https://aclanthology.org/2024.acl-short.9/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
91. [TMU-HIT''s Submission for the WMT24 Quality Estimation Shared Task: Is GPT-4 a Good Evaluator for Machine Translation?](https://aclanthology.org/2024.wmt-1.38/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*
92. [Themis: A Reference-free NLG Evaluation Language Model with Flexibility and Interpretability](https://aclanthology.org/2024.emnlp-main.891/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
93. [Towards Large Language Model driven Reference-less Translation Evaluation for English and Indian Languages](https://arxiv.org/abs/2404.02512) *— 2024 · arXiv:2404.02512*
94. [Towards Multiple References Era – Addressing Data Leakage and Limited Reference Diversity in Machine Translation Evaluation](https://aclanthology.org/2024.findings-acl.710/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
95. [Towards Precise Localization of Critical Errors in Machine Translation](https://aclanthology.org/2024.findings-acl.177/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
96. [Towards a More Comprehensive Evaluation for Italian LLMs](https://aclanthology.org/2024.clicit-1.67/) *— 2024 · Proceedings of the Tenth Italian Conference on Computational Linguistics (CLiC-it 2024)*
97. [TransAgents: Build Your Translation Company with Language Agents](https://aclanthology.org/2024.emnlp-demo.14/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
98. [Word-level Translation Quality Estimation Based on Optimal Transport](https://aclanthology.org/2024.amta-research.18/) *— 2024 · Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
99. [adaptMLLM: Fine-Tuning Multilingual Language Models on Low-Resource Languages with Integrated LLM Playgrounds](https://arxiv.org/abs/2403.02370) *— 2024 · arXiv:2403.02370 · Information 2023, 14(12), 638*
100. [chrF-S: Semantics Is All You Need](https://aclanthology.org/2024.wmt-1.33/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*

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