---
title: "Who cites Experts, Errors, and Context: A Large-Scale…"
description: "The papers of the Elamur Research library that cite «Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation», found…"
canonical: "https://research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/cited-by/page/2/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/cited-by/page/2/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Experts, Errors, and Context: A Large-Scale Study…](https://md.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/) / cited by

# 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.research.elamur.ai/free/en/papers/freitag-2021-experts-errors-context-large-scale/)

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

1. [Feeding Two Birds or Favoring One? Adequacy-Fluency Tradeoffs in Evaluation and Meta-Evaluation of Machine Translation](https://arxiv.org/abs/2509.20287) *— 2025 · arXiv:2509.20287*
2. [Feeding Two Birds or Favoring One? Adequacy–Fluency Tradeoffs in Evaluation and Meta-Evaluation of Machine Translation](https://aclanthology.org/2025.wmt-1.16/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
3. [Findings of the First Patent Claims Translation Task at WAT2025](https://aclanthology.org/2025.wat-1.1/) *— 2025 · Proceedings of the Twelfth Workshop on Asian Translation (WAT 2025)*
4. [Findings of the IWSLT 2025 Evaluation Campaign](https://aclanthology.org/2025.iwslt-1.44/) *— 2025 · Proceedings of the 22nd International Conference on Spoken Language Translation (IWSLT 2025)*
5. [Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets](https://aclanthology.org/2025.wmt-1.22/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
6. [Findings of the WMT25 Multilingual Instruction Shared Task: Persistent Hurdles in Reasoning, Generation, and Evaluation](https://aclanthology.org/2025.wmt-1.23/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
7. [Findings of the WMT25 Shared Task on Automated Translation Evaluation Systems: Linguistic Diversity is Challenging and References Still Help](https://aclanthology.org/2025.wmt-1.24/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
8. [From NLG Evaluation to Modern Student Assessment in the Era of ChatGPT: The Great Misalignment Problem and Pedagogical Multi-Factor Assessment (P-MFA)](https://aclanthology.org/2025.iwclul-1.1/) *— 2025 · Proceedings of the 10th International Workshop on Computational Linguistics for Uralic Languages*
9. [Gender Bias in English-to-Greek Machine Translation](https://aclanthology.org/2025.gitt-1.2/) *— 2025 · Proceedings of the 3rd Workshop on Gender-Inclusive Translation Technologies (GITT 2025)*
10. [HISTOIRESMORALES: A French Dataset for Assessing Moral Alignment](https://aclanthology.org/2025.naacl-long.131/) *— 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)*
11. [Has Machine Translation Evaluation Achieved Human Parity? The Human Reference and the Limits of Progress](https://aclanthology.org/2025.acl-short.63/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
12. [HiMATE: A Hierarchical Multi-Agent Framework for Machine Translation Evaluation](https://aclanthology.org/2025.findings-emnlp.593/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
13. [How Good Are LLMs for Literary Translation, Really? Literary Translation Evaluation with Humans and LLMs](https://aclanthology.org/2025.naacl-long.548/) *— 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)*
14. [How Well Do Large Reasoning Models Translate? A Comprehensive Evaluation for Multi-Domain Machine Translation](https://arxiv.org/abs/2505.19987) *— 2025 · arXiv:2505.19987*
15. [How to Evaluate Speech Translation with Source-Aware Neural MT Metrics](https://arxiv.org/abs/2511.03295) *— 2025 · arXiv:2511.03295*
16. [IRB-MT at WMT25 Translation Task: A Simple Agentic System Using an Off-the-Shelf LLM](https://aclanthology.org/2025.wmt-1.51/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
17. [LLMs for Low-Resource Dialect Translation Using Context-Aware Prompting: A Case Study on Sylheti](https://aclanthology.org/2025.banglalp-1.24/) *— 2025 · Proceedings of the Second Workshop on Bangla Language Processing (BLP-2025)*
18. [La traduction automatique dialectale: état de l”art et étude préliminaire sur le continuum dialectal de l”occitan](https://aclanthology.org/2025.jeptalnrecital-recital.12/) *— 2025 · Actes des 18e Rencontres Jeunes Chercheurs en RI (RJCRI) et 27ème Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL)*
19. [LiTransProQA: An LLM-based Literary Translation Evaluation Metric with Professional Question Answering](https://aclanthology.org/2025.emnlp-main.1482/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
20. [Localizing and Mitigating Errors in Long-form Question Answering](https://aclanthology.org/2025.findings-acl.1049/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
21. [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)*
22. [MAATS: A Multi-Agent Automated Translation System Based on MQM Evaluation](https://arxiv.org/abs/2505.14848) *— 2025 · arXiv:2505.14848*
23. [MAS-LitEval : Multi-Agent System for Literary Translation Quality Assessment](https://arxiv.org/abs/2506.14199) *— 2025 · arXiv:2506.14199*
24. [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*
25. [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*
26. [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)*
27. [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*
28. [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*
29. [Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets](https://aclanthology.org/2025.cl-1.4/) *— 2025 · Computational Linguistics*
30. [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*
31. [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*
32. [Non-Linear Scoring Model for Translation Quality Evaluation](https://arxiv.org/abs/2511.13467) *— 2025 · arXiv:2511.13467*
33. [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*
34. [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*
35. [Penalizing Length: Uncovering Systematic Bias in Quality Estimation Metrics](https://arxiv.org/abs/2510.22028) *— 2025 · arXiv:2510.22028*
36. [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)*
37. [QE4PE: Word-level Quality Estimation for Human Post-Editing](https://aclanthology.org/2025.tacl-1.64/) *— 2025 · Transactions of the Association for Computational Linguistics*
38. [Quality Estimation Reranking for Document-Level Translation](https://arxiv.org/abs/2510.08870) *— 2025 · arXiv:2510.08870*
39. [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)*
40. [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*
41. [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)*
42. [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*
43. [Rubrik”s Cube: Testing a New Rubric for Evaluating Explanations on the CUBE dataset](https://aclanthology.org/2025.acl-long.1160/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
44. [Self-Vocabularizing Training for Neural Machine Translation](https://aclanthology.org/2025.naacl-srw.16/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)*
45. [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*
46. [Structured Document Translation via Format Reinforcement Learning](https://aclanthology.org/2025.ijcnlp-long.38/) *— 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
47. [SwissADT: An Audio Description Translation System for Swiss Languages](https://aclanthology.org/2025.naacl-industry.31/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track)*
48. [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*
49. [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*
50. [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*
51. [Toward Global AI Inclusivity: A Large-Scale Multilingual Terminology Dataset (GIST)](https://aclanthology.org/2025.findings-acl.1148/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
52. [Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations](https://aclanthology.org/2025.emnlp-main.1725/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
53. [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)*
54. [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*
55. [Two Step Automatic Post Editing of Patent Machine Translation based on Pre-trained Encoder Models and LLMs](https://aclanthology.org/2025.ijcnlp-srw.19/) *— 2025 · The 14th International Joint Conference on Natural Language Processing and The 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
56. [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*
57. [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)*
58. [VELA: An LLM-Hybrid-as-a-Judge Approach for Evaluating Long Image Captions](https://aclanthology.org/2025.emnlp-main.438/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
59. [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*
60. [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*
61. [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)*
62. [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*
63. [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)*
64. [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)*
65. [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)*
66. [BMX: Boosting Natural Language Generation Metrics with Explainability](https://aclanthology.org/2024.findings-eacl.150/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
67. [Barriers to Effective Evaluation of Simultaneous Interpretation](https://aclanthology.org/2024.findings-eacl.15/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
68. [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*
69. [Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics](https://md.research.elamur.ai/free/en/papers/perrella-2024-beyond-correlation-interpretable-evaluation-machine/) *— our card · 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
70. [Beyond Human-Only: Evaluating Human-Machine Collaboration for Collecting High-Quality Translation Data](https://aclanthology.org/2024.wmt-1.110/) *— 2024 · Proceedings of the Ninth Conference on Machine Translation*
71. [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*
72. [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)*
73. [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*
74. [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)*
75. [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*
76. [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*
77. [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)*
78. [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*
79. [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*
80. [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*
81. [Evading Data Contamination Detection for Language Models is (too) Easy](https://arxiv.org/abs/2402.02823) *— 2024 · arXiv:2402.02823*
82. [Evaluation Briefs: Drawing on Translation Studies for Human Evaluation of MT](https://aclanthology.org/2024.amta-research.17/) *— 2024 · Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
83. [Evaluation and Continual Improvement for an Enterprise AI Assistant](https://aclanthology.org/2024.dash-1.3/) *— 2024 · Proceedings of the Fifth Workshop on Data Science with Human-in-the-Loop (DaSH 2024)*
84. [Exploring Human-Like Translation Strategy with Large Language Models](https://aclanthology.org/2024.tacl-1.13/) *— 2024 · Transactions of the Association for Computational Linguistics*
85. [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)*
86. [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)*
87. [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)*
88. [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)*
89. [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*
90. [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*
91. [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)*
92. [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*
93. [HD-Eval: Aligning Large Language Model Evaluators Through Hierarchical Criteria Decomposition](https://aclanthology.org/2024.acl-long.413/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
94. [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)*
95. [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*
96. [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*
97. [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*
98. [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*
99. [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*
100. [LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods](https://arxiv.org/abs/2412.05579) *— 2024 · arXiv:2412.05579*

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