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# Who cites «Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation» · page 3

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/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/freitag-2021-experts-errors-context-large-scale/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/freitag-2021-experts-errors-context-large-scale-2/) · **3** · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/freitag-2021-experts-errors-context-large-scale-4/)

1. [xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection](https://aclanthology.org/2024.tacl-1.54/) *— 2024 · Transactions of the Association for Computational Linguistics*
2. [A Critical Evaluation of Evaluations for Long-form Question Answering](https://aclanthology.org/2023.acl-long.181/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [An Experiment in Error Analysis of Real-time Speech Machine Translation Using the Example of the European Parliament's Innovation Partnership](https://aclanthology.org/2023.clicit-1.24/) *— 2023 · Proceedings of the Ninth Italian Conference on Computational Linguistics (CLiC-it 2023)*
4. [Are Experts Needed? On Human Evaluation of Counselling Reflection Generation](https://aclanthology.org/2023.acl-long.382/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
5. [AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ](https://arxiv.org/abs/2310.00367) *— 2023 · arXiv:2310.00367 · The Twelfth International Conference on Learning Representations, 2024*
6. [BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models](https://arxiv.org/abs/2309.06085) *— 2023 · arXiv:2309.06085*
7. [Barriers and enabling factors for error analysis in NLG research](https://nejlt.ep.liu.se/article/view/4529) *— 2023 · Northern European Journal of Language Technology*
8. [Beyond Correlation: Making Sense of the Score Differences of New MT Evaluation Metrics](https://aclanthology.org/2023.mtsummit-research.16/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 1: Research Track*
9. [BooookScore: A systematic exploration of book-length summarization in the era of LLMs](https://arxiv.org/abs/2310.00785) *— 2023 · arXiv:2310.00785*
10. [Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://aclanthology.org/2023.tacl-1.92/) *— 2023*
11. [CCEval: A Representative Evaluation Benchmark for the Chinese-centric Multilingual Machine Translation](https://aclanthology.org/2023.findings-emnlp.682/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
12. [Dancing Between Success and Failure: Edit-level Simplification Evaluation using SALSA](https://aclanthology.org/2023.emnlp-main.211/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
13. [DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence](https://aclanthology.org/2023.eacl-main.278/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
14. [Document Flattening: Beyond Concatenating Context for Document-Level Neural Machine Translation](https://aclanthology.org/2023.eacl-main.33/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
15. [Empirical Assessment of kNN-MT for Real-World Translation Scenarios](https://aclanthology.org/2023.eamt-1.12/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
16. [Epsilon Sampling Rocks: Investigating Sampling Strategies for Minimum Bayes Risk Decoding for Machine Translation](https://aclanthology.org/2023.findings-emnlp.617/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
17. [Evaluating Optimal Reference Translations](https://arxiv.org/abs/2311.16787) *— 2023 · arXiv:2311.16787*
18. [Explaining with Contrastive Phrasal Highlighting: A Case Study in Assisting Humans to Detect Translation Differences](https://aclanthology.org/2023.emnlp-main.690/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
19. [Extrinsic Evaluation of Machine Translation Metrics](https://aclanthology.org/2023.acl-long.730/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
20. [FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN](https://aclanthology.org/2023.iwslt-1.1/) *— 2023 · Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)*
21. [FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation](https://aclanthology.org/2023.tacl-1.39/) *— 2023 · Transactions of the Association for Computational Linguistics*
22. [Findings of the 2023 Conference on Machine Translation (WMT23): LLMs Are Here but Not Quite There Yet](https://aclanthology.org/2023.wmt-1.1/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
23. [Findings of the WMT 2023 Shared Task on Quality Estimation](https://aclanthology.org/2023.wmt-1.52/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
24. [GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4](https://aclanthology.org/2023.wmt-1.64/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
25. [GPTScore: Evaluate as You Desire](https://arxiv.org/abs/2302.04166) *— 2023 · arXiv:2302.04166*
26. [How effective is machine translation on low-resource code-switching? A case study comparing human and automatic metrics](https://aclanthology.org/2023.findings-acl.893/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
27. [INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback](https://aclanthology.org/2023.emnlp-main.365/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
28. [IOL Research's Submission for WMT 2023 Quality Estimation Shared Task](https://aclanthology.org/2023.wmt-1.76/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
29. [IndicMT Eval: A Dataset to Meta-Evaluate Machine Translation Metrics for Indian Languages](https://aclanthology.org/2023.acl-long.795/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Large Language Models Are State-of-the-Art Evaluators of Translation Quality](https://aclanthology.org/2023.eamt-1.19/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
31. [Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist](https://aclanthology.org/2023.wmt-1.41/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
32. [Leveraging GPT-4 for Automatic Translation Post-Editing](https://aclanthology.org/2023.findings-emnlp.804/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
33. [MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods](https://arxiv.org/abs/2309.10966) *— 2023 · arXiv:2309.10966*
34. [MMT's Submission for the WMT 2023 Quality Estimation Shared Task](https://aclanthology.org/2023.wmt-1.75/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
35. [MetricX-23: The Google Submission to the WMT 2023 Metrics Shared Task](https://aclanthology.org/2023.wmt-1.63/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
36. [NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist](https://aclanthology.org/2023.acl-long.69/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
37. [Onception: Active Learning with Expert Advice for Real World Machine Translation](https://aclanthology.org/2023.cl-2.3/) *— 2023 · Computational Linguistics*
38. [PE effort and neural-based automatic MT metrics: do they correlate?](https://aclanthology.org/2023.eamt-1.31/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
39. [PaLM 2 Technical Report](https://arxiv.org/abs/2305.10403) *— 2023 · arXiv:2305.10403*
40. [ParroT: Translating during Chat using Large Language Models tuned with Human Translation and Feedback](https://aclanthology.org/2023.findings-emnlp.1001/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
41. [Physician Detection of Clinical Harm in Machine Translation: Quality Estimation Aids in Reliance and Backtranslation Identifies Critical Errors](https://aclanthology.org/2023.emnlp-main.712/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
42. [Prompting PaLM for Translation: Assessing Strategies and Performance](https://aclanthology.org/2023.acl-long.859/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
43. [Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent](https://aclanthology.org/2023.wmt-1.51/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
44. [Rethinking the Word-level Quality Estimation for Machine Translation from Human Judgement](https://aclanthology.org/2023.findings-acl.126/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
45. [Reward Gaming in Conditional Text Generation](https://aclanthology.org/2023.acl-long.262/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
46. [SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation](https://aclanthology.org/2023.emnlp-main.584/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
47. [SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes](https://aclanthology.org/2023.acl-long.283/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [Student''s t-Distribution: On Measuring the Inter-Rater Reliability When the Observations are Scarce](https://aclanthology.org/2023.ranlp-1.47/) *— 2023 · Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing*
49. [T5Score: Discriminative Fine-tuning of Generative Evaluation Metrics](https://aclanthology.org/2023.findings-emnlp.1014/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
50. [TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks](https://arxiv.org/abs/2310.00752) *— 2023 · arXiv:2310.00752*
51. [Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization](https://aclanthology.org/2023.acl-long.47/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
52. [The Best of Both Worlds: Combining Human and Machine Translations for Multilingual Semantic Parsing with Active Learning](https://aclanthology.org/2023.acl-long.529/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
53. [The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation](https://aclanthology.org/2023.wmt-1.100/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
54. [The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics](https://aclanthology.org/2023.eval4nlp-1.10/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
55. [The MT@BZ corpus: machine translation & legal language](https://aclanthology.org/2023.eamt-1.17/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
56. [Thresh: A Unified, Customizable and Deployable Platform for Fine-Grained Text Evaluation](https://aclanthology.org/2023.emnlp-demo.30/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
57. [Ties Matter: Meta-Evaluating Modern Metrics with Pairwise Accuracy and Tie Calibration](https://aclanthology.org/2023.emnlp-main.798/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
58. [Toward Human-Like Evaluation for Natural Language Generation with Error Analysis](https://aclanthology.org/2023.acl-long.324/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
59. [Towards Explainable Evaluation Metrics for Machine Translation](https://arxiv.org/abs/2306.13041) *— 2023 · arXiv:2306.13041 · Journal of Machine Learning Research (JMLR), 2024, vol. 25, no. 75, p. 1-49*
60. [Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors](https://arxiv.org/abs/2302.08975) *— 2023 · arXiv:2302.08975*
61. [Towards Large Language Model driven Reference-less Translation Evaluation for English and Indian Language](https://aclanthology.org/2023.icon-1.28/) *— 2023 · Proceedings of the 20th International Conference on Natural Language Processing (ICON)*
62. [Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents](https://aclanthology.org/2023.emnlp-main.835/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
63. [Toxicity in Multilingual Machine Translation at Scale](https://aclanthology.org/2023.findings-emnlp.642/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
64. [Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level](https://aclanthology.org/2023.wmt-1.96/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
65. [UScore: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translation](https://aclanthology.org/2023.eacl-main.27/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
66. [eBLEU: Unexpectedly Good Machine Translation Evaluation Using Simple Word Embeddings](https://aclanthology.org/2023.wmt-1.61/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
67. [A Comparison of Data Filtering Methods for Neural Machine Translation](https://aclanthology.org/2022.amta-upg.22/) *— 2022 · Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)*
68. [A Natural Diet: Towards Improving Naturalness of Machine Translation Output](https://aclanthology.org/2022.findings-acl.263/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
69. [A new approach to calculating BERTScore for automatic assessment of translation quality](https://arxiv.org/abs/2203.05598) *— 2022 · arXiv:2203.05598*
70. [ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics](https://md.mova.elamur.ai/free/en/docs/papers/amrhein-2022-aces-translation-accuracy-challenge-sets/) *— our card · 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
71. [Alibaba-Translate China's Submission for WMT 2022 Metrics Shared Task](https://arxiv.org/abs/2210.09683) *— 2022 · arXiv:2210.09683*
72. [Alibaba-Translate China's Submission for WMT 2022 Quality Estimation Shared Task](https://aclanthology.org/2022.wmt-1.55/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
73. [Alibaba-Translate China's Submission for WMT2022 Metrics Shared Task](https://aclanthology.org/2022.wmt-1.53/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
74. [An Overview on Machine Translation Evaluation](https://arxiv.org/abs/2202.11027) *— 2022 · arXiv:2202.11027*
75. [As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning](https://aclanthology.org/2022.acl-short.53/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
76. [Automatic Correction of Human Translations](https://aclanthology.org/2022.naacl-main.36/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
77. [BJTU-Toshiba's Submission to WMT22 Quality Estimation Shared Task](https://aclanthology.org/2022.wmt-1.58/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
78. [Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand](https://aclanthology.org/2022.naacl-main.259/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
79. [COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task](https://aclanthology.org/2022.wmt-1.52/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
80. [CometKiwi: IST-Unbabel 2022 Submission for the Quality Estimation Shared Task](https://aclanthology.org/2022.wmt-1.60/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
81. [Consistent Human Evaluation of Machine Translation across Language Pairs](https://aclanthology.org/2022.amta-research.24/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
82. [Disentangling Uncertainty in Machine Translation Evaluation](https://aclanthology.org/2022.emnlp-main.591/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
83. [DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages](https://aclanthology.org/2022.emnlp-main.532/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
84. [Does Summary Evaluation Survive Translation to Other Languages?](https://aclanthology.org/2022.naacl-main.173/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
85. [Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric into a Document-Level Metric](https://aclanthology.org/2022.wmt-1.6/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
86. [Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark](https://aclanthology.org/2022.tacl-1.62/) *— 2022 · Transactions of the Association for Computational Linguistics*
87. [Evaluating Machine Translation in Cross-lingual E-Commerce Search](https://aclanthology.org/2022.amta-research.25/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
88. [Examining Large Pre-Trained Language Models for Machine Translation: What You Don''t Know about It](https://aclanthology.org/2022.wmt-1.84/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
89. [Findings of the 2022 Conference on Machine Translation (WMT22)](https://aclanthology.org/2022.wmt-1.1/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
90. [Findings of the First WMT Shared Task on Sign Language Translation (WMT-SLT22)](https://aclanthology.org/2022.wmt-1.71/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
91. [Findings of the IWSLT 2022 Evaluation Campaign](https://aclanthology.org/2022.iwslt-1.10/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
92. [Findings of the WMT 2022 Shared Task on Chat Translation](https://aclanthology.org/2022.wmt-1.70/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
93. [Findings of the WMT 2022 Shared Task on Efficient Translation](https://aclanthology.org/2022.wmt-1.4/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
94. [From COMET to COMES – Can Summary Evaluation Benefit from Translation Evaluation?](https://aclanthology.org/2022.eval4nlp-1.3/) *— 2022 · Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems*
95. [GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation](https://aclanthology.org/2022.emnlp-main.787/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
96. [HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation](https://aclanthology.org/2022.lrec-1.2/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
97. [High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics](https://aclanthology.org/2022.tacl-1.47/) *— 2022 · Transactions of the Association for Computational Linguistics*
98. [HilMeMe: A Human-in-the-Loop Machine Translation Evaluation Metric Looking into Multi-Word Expressions](https://arxiv.org/abs/2211.05201) *— 2022 · arXiv:2211.05201*
99. [Identifying Weaknesses in Machine Translation Metrics Through Minimum Bayes Risk Decoding: A Case Study for COMET](https://aclanthology.org/2022.aacl-main.83/) *— 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
100. [MS-COMET: More and Better Human Judgements Improve Metric Performance](https://aclanthology.org/2022.wmt-1.47/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*

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