---
title: "Who cites Results of WMT22 Metrics Shared Task: Stop Using…"
description: "The papers of the Elamur Research library that cite «Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust»…"
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---
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# Who cites «Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust»

251 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-2022-results-wmt22-metrics-shared-task/)

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1. [Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations](https://aclanthology.org/2026.eamt-1.43/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
2. [Diagnose, Then Repair: A Two-Stage MQM-Guided Post-Editing Framework for Domain-Specific Machine Translation](https://aclanthology.org/2026.acl-industry.115/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)*
3. [Document Summarization for AI-based Post-Editing](https://aclanthology.org/2026.amta-research.11/) *— 2026 · Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
4. [Dynamic Meta-Metrics: Source-Sentence Conditioned Weighting for MT Evaluation](https://aclanthology.org/2026.acl-srw.80/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
5. [Evaluating LLM-Based Translation of a Low-Resource Technical Language: The Medical and Philosophical Greek of Galen](https://arxiv.org/abs/2602.24119) *— 2026 · arXiv:2602.24119*
6. [Evaluating Large Language Models for Hausa and Fongbe Machine Translation: Benchmarks, Failures, and Metric Reliability](https://arxiv.org/abs/2606.22269) *— 2026 · arXiv:2606.22269*
7. [From Outliers to Errors: Auditing Pali-to-English LLM Translations with Multi-Reference Adjudication](https://arxiv.org/abs/2606.01136) *— 2026 · arXiv:2606.01136*
8. [From Words to Worlds: Benchmarking Cross-Cultural Cultural Understanding in Machine Translation](https://arxiv.org/abs/2603.17303) *— 2026 · arXiv:2603.17303*
9. [Grammar as Control: Modular Language Generation for the Long Tail](https://aclanthology.org/2026.acl-long.1725/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
10. [HydraQE: OSU”s Submission for the IWSLT 2026 Speech Translation Metrics Shared Task](https://aclanthology.org/2026.iwslt-1.37/) *— 2026 · Proceedings of the 23rd International Conference on Spoken Language Translation (IWSLT 2026)*
11. [Is Human Annotation Necessary? Iterative MBR Distillation for Error Span Detection in Machine Translation](https://arxiv.org/abs/2603.12983) *— 2026 · arXiv:2603.12983*
12. [JP-TL-Bench: Anchored Pairwise LLM Evaluation for Bidirectional Japanese-English Translation](https://arxiv.org/abs/2601.00223) *— 2026 · arXiv:2601.00223*
13. [KinyCOMET: Automatic Evaluation of Machine Translation Systems for Kinyarwanda–English](https://aclanthology.org/2026.lrec-1.383/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
14. [LLM as a Meta-Judge: Synthetic Data for NLP Evaluation Metric Validation](https://aclanthology.org/2026.acl-srw.125/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)*
15. [Large Language Models as Annotators for Machine Translation Quality Estimation](https://arxiv.org/abs/2603.10775) *— 2026 · arXiv:2603.10775*
16. [MO-GRPO: Mitigating Reward Hacking of Group Relative Policy Optimization on Multi-Objective Problems](https://aclanthology.org/2026.tacl-1.84/) *— 2026 · Transactions of the Association for Computational Linguistics*
17. [MQM Re-Annotation: A Technique for Collaborative Evaluation of Machine Translation](https://aclanthology.org/2026.acl-long.1553/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
18. [MT$^3$: A Synergistic Multi-Task RL Framework for Specializing MLLMs in Text Image Machine Translation](https://aclanthology.org/2026.acl-long.460/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
19. [MeSHClass-ES and AnatEM-ES: Open Resources for Spanish Biomedical NLP](https://aclanthology.org/2026.bionlp-1.49/) *— 2026 · BioNLP 2026*
20. [MetaDocEval: A Contrastive Framework for Evaluating Machine Translation Metrics at the Document-Level](https://aclanthology.org/2026.eamt-1.19/) *— 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)*
21. [Mind Which Bird You Favour: Parameterizing Adequacy-Fluency Balance in Meta-Evaluation of Machine Translation](https://arxiv.org/abs/2609.14795) *— 2026 · arXiv:2609.14795*
22. [Never Truly Out of Fashion: A Retrospective Look at Evaluation in NLG](https://aclanthology.org/2026.retroeval-main.8/) *— 2026 · Proceedings of the 1st Symposium on Natural Language Generation Evaluations*
23. [One Pair Suffices: Unlocking Universal Zero-Shot Translation via Cross-Architecture Alignment](https://aclanthology.org/2026.acl-long.1912/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
24. [PaliBench: A Multi-Reference Blueprint for Classical Language Translation Benchmarks](https://arxiv.org/abs/2605.16881) *— 2026 · arXiv:2605.16881*
25. [Professional Translators Versus Quality Estimation Models: Reliability and Agreement in English-Ukrainian Translation Evaluation](https://aclanthology.org/2026.unlp-1.10/) *— 2026 · Proceedings of the Fifth Ukrainian Natural Language Processing Conference (UNLP 2026)*
26. [Remedy-R: Generative Reasoning for Machine Translation Evaluation without Error Annotations](https://aclanthology.org/2026.findings-acl.364/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
27. [Scoring the Translation: On Target Automatic Keyword-Based Evaluation of Machine Translation in the Sports Domain](https://aclanthology.org/2026.lrec-1.697/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
28. [Semantic Fidelity Versus Literary Quality: A Construct Validity Study of Neural Machine Translation Metrics](https://aclanthology.org/2026.unlp-1.8/) *— 2026 · Proceedings of the Fifth Ukrainian Natural Language Processing Conference (UNLP 2026)*
29. [Span-Level Machine Translation Meta-Evaluation](https://arxiv.org/abs/2603.19921) *— 2026 · arXiv:2603.19921*
30. [SrcMix: Mixing of Related Source Languages Benefits Extremely Low-resource Machine Translation](https://aclanthology.org/2026.findings-eacl.332/) *— 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
31. [TQLite: Multi-LLM Jury Guided Distillation for Real-time MQM Translation Quality Evaluation](https://arxiv.org/abs/2608.02975) *— 2026 · arXiv:2608.02975*
32. [VietMix: A Naturally-Occurring Parallel Corpus and Augmentation Framework for Vietnamese-English Code-Mixed Machine Translation](https://aclanthology.org/2026.eacl-long.342/) *— 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
33. [Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains](https://aclanthology.org/2026.findings-acl.1145/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
34. [(Dis)improved?! How Simplified Language Affects Large Language Model Performance across Languages](https://aclanthology.org/2025.gem-1.70/) *— 2025 · Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM\texttwosuperior)*
35. [A Representation Level Analysis of NMT Model Robustness to Grammatical Errors](https://aclanthology.org/2025.findings-acl.451/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
36. [Adding Chocolate to Mint: Mitigating Metric Interference in Machine Translation](https://aclanthology.org/2025.tacl-1.60/) *— 2025 · Transactions of the Association for Computational Linguistics*
37. [Analyzing and Evaluating Correlation Measures in NLG Meta-Evaluation](https://aclanthology.org/2025.naacl-long.111/) *— 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)*
38. [Are Generative Models Underconfident? Better Quality Estimation with Boosted Model Probability](https://aclanthology.org/2025.emnlp-main.166/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
39. [Auto-Weighted Group Relative Preference Optimization for Multi-Objective Text Generation Tasks](https://aclanthology.org/2025.emnlp-industry.80/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track*
40. [BLEUBERI: BLEU is a surprisingly effective reward for instruction following](https://arxiv.org/abs/2505.11080) *— 2025 · arXiv:2505.11080*
41. [Better Late Than Never: Meta-Evaluation of Latency Metrics for Simultaneous Speech-to-Text Translation](https://arxiv.org/abs/2509.17349) *— 2025 · arXiv:2509.17349*
42. [COMET-poly: Machine Translation Metric Grounded in Other Candidates](https://aclanthology.org/2025.wmt-1.63/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
43. [CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation](https://aclanthology.org/2025.findings-acl.31/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
44. [Calibrating Translation Decoding with Quality Estimation on LLMs](https://arxiv.org/abs/2504.19044) *— 2025 · arXiv:2504.19044*
45. [Code-Switching Curriculum Learning for Multilingual Transfer in LLMs](https://aclanthology.org/2025.findings-acl.407/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
46. [Conditions for Catastrophic Forgetting in Multilingual Translation](https://aclanthology.org/2025.mrl-main.23/) *— 2025 · Proceedings of the 5th Workshop on Multilingual Representation Learning (MRL 2025)*
47. [Contextual Metric Meta-Evaluation by Measuring Local Metric Accuracy](https://aclanthology.org/2025.findings-naacl.276/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
48. [ContrastScore: Towards Higher Quality, Less Biased, More Efficient Evaluation Metrics with Contrastive Evaluation](https://aclanthology.org/2025.ijcnlp-long.163/) *— 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*
49. [Conveying Imagistic Thinking in Traditional Chinese Medicine Translation: A Prompt Engineering and LLM-Based Evaluation Framework](https://arxiv.org/abs/2511.23059) *— 2025 · arXiv:2511.23059*
50. [D\”ejà Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation](https://arxiv.org/abs/2504.11829) *— 2025 · arXiv:2504.11829*
51. [Diversity Explains Inference Scaling Laws: Through a Case Study of Minimum Bayes Risk Decoding](https://aclanthology.org/2025.acl-long.1410/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
52. [Do LLMs Understand Wine Descriptors Across Cultures? A Benchmark for Cultural Adaptations of Wine Reviews](https://aclanthology.org/2025.findings-emnlp.99/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
53. [Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport](https://aclanthology.org/2025.acl-long.1370/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
54. [Don”t Sweat the Small Stuff: Segment-Level Meta-Evaluation Based on Pairwise Difference Correlation](https://aclanthology.org/2025.emnlp-main.1273/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
55. [Efficient Architectures For Low-Resource Machine Translation](https://aclanthology.org/2025.lowresnlp-1.6/) *— 2025 · Proceedings of the First Workshop on Advancing NLP for Low-Resource Languages*
56. [Evaluating Language Translation Models by Playing Telephone](https://aclanthology.org/2025.emnlp-main.524/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
57. [Evaluating Synthetic Data Generation from User Generated Text](https://aclanthology.org/2025.cl-1.6/) *— 2025 · Computational Linguistics*
58. [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*
59. [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*
60. [FinGrAct: A Framework for FINe-GRrained Evaluation of ACTionability in Explainable Automatic Fact-Checking](https://aclanthology.org/2025.findings-emnlp.525/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
61. [Generative AI for Technical Writing: Comparing Human and LLM Assessments of Generated Content](https://aclanthology.org/2025.nodalida-1.67/) *— 2025 · Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)*
62. [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)*
63. [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*
64. [How to Evaluate Speech Translation with Source-Aware Neural MT Metrics](https://arxiv.org/abs/2511.03295) *— 2025 · arXiv:2511.03295*
65. [How to Select Datapoints for Efficient Human Evaluation of NLG Models?](https://aclanthology.org/2025.tacl-1.80/) *— 2025 · Transactions of the Association for Computational Linguistics*
66. [IberoBench: A Benchmark for LLM Evaluation in Iberian Languages](https://aclanthology.org/2025.coling-main.699/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
67. [Incorporating Target Fuzzy Matches into Neural Fuzzy Repair](https://aclanthology.org/2025.nodalida-1.44/) *— 2025 · Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)*
68. [Intrinsic vs. Extrinsic Evaluation of Czech Sentence Embeddings: Semantic Relevance Doesn”t Help with MT Evaluation](https://aclanthology.org/2025.mtsummit-1.20/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
69. [LLMs Are Not Scorers: Rethinking MT Evaluation with Generation-Based Methods](https://arxiv.org/abs/2505.16129) *— 2025 · arXiv:2505.16129*
70. [Long-context Reference-based MT Quality Estimation](https://aclanthology.org/2025.wmt-1.64/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
71. [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)*
72. [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*
73. [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)*
74. [MSLC25: Metric Performance on Low-Quality Machine Translation, Empty Strings, and Language Variants](https://aclanthology.org/2025.wmt-1.69/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
75. [Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets](https://aclanthology.org/2025.cl-1.4/) *— 2025 · Computational Linguistics*
76. [Marco Large Translation Model at WMT2025: Transforming Translation Capability in LLMs via Quality-Aware Training and Decoding](https://aclanthology.org/2025.wmt-1.33/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
77. [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*
78. [Prompt Engineering Enhances Faroese MT, but Only Humans Can Tell](https://aclanthology.org/2025.nodalida-1.63/) *— 2025 · Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)*
79. [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)*
80. [Quality Estimation Reranking for Document-Level Translation](https://arxiv.org/abs/2510.08870) *— 2025 · arXiv:2510.08870*
81. [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*
82. [SHuBERT: Self-Supervised Sign Language Representation Learning via Multi-Stream Cluster Prediction](https://aclanthology.org/2025.acl-long.1397/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
83. [Simulstream: Open-Source Toolkit for Evaluation and Demonstration of Streaming Speech-to-Text Translation Systems](https://arxiv.org/abs/2512.17648) *— 2025 · arXiv:2512.17648*
84. [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*
85. [Targeted Source Text Editing for Machine Translation: Exploiting Quality Estimators and Large Language Models](https://aclanthology.org/2025.wmt-1.12/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
86. [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*
87. [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*
88. [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*
89. [A Preference-driven Paradigm for Enhanced Translation with Large Language Models](https://aclanthology.org/2024.naacl-long.186/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
90. [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)*
91. [Aligning Neural Machine Translation Models: Human Feedback in Training and Inference](https://aclanthology.org/2024.eamt-1.22/) *— 2024 · Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)*
92. [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)*
93. [Anti-LM Decoding for Zero-shot In-context Machine Translation](https://aclanthology.org/2024.findings-naacl.216/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
94. [Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine Translation](https://aclanthology.org/2024.tacl-1.22/) *— 2024 · Transactions of the Association for Computational Linguistics*
95. [Assessing the Role of Context in Chat Translation Evaluation: Is Context Helpful and Under What Conditions?](https://aclanthology.org/2024.tacl-1.69/) *— 2024 · Transactions of the Association for Computational Linguistics*
96. [Barriers to Effective Evaluation of Simultaneous Interpretation](https://aclanthology.org/2024.findings-eacl.15/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
97. [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*
98. [Benchmarking the Performance of Machine Translation Evaluation Metrics with Chinese Multiword Expressions](https://aclanthology.org/2024.lrec-main.198/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
99. [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*
100. [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*

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