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# Who cites «A Structured Review of the Validity of BLEU»

162 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/reiter-2018-structured-review-validity-bleu/)

Pages: **1** · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/reiter-2018-structured-review-validity-bleu-2/)

1. [Benchmarking Bengali Dialectal Bias: A Multi-Stage Framework Integrating RAG-Based Translation and Human-Augmented RLAIF](https://arxiv.org/abs/2603.21359) *— 2026 · arXiv:2603.21359*
2. [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*
3. [JP-TL-Bench: Anchored Pairwise LLM Evaluation for Bidirectional Japanese-English Translation](https://arxiv.org/abs/2601.00223) *— 2026 · arXiv:2601.00223*
4. [LLM as a law professor: having a large language model write a commentary on freedom of assembly](https://doi.org/10.1007/s10506-026-09527-4) *— 2026 · Artificial Intelligence and Law (Springer)*
5. [OasisSimp: An Open-source Asian-English Sentence Simplification Dataset](https://aclanthology.org/2026.lrec-1.483/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
6. [Position: What Are We Measuring? Rethinking Evaluation in Natural Language Generation](https://aclanthology.org/2026.gem-main.79/) *— 2026 · Proceedings of the Fifth Workshop on Generation, Evaluation and Metrics (GEM)*
7. [Referenceless Evaluation of Machine Translation Models by Ranking Performance in Romanian to English Translate-train Settings](https://aclanthology.org/2026.lrec-1.693/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
8. [Awes, Laws, and Flaws From Today's LLM Research](https://aclanthology.org/2025.findings-acl.664/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
9. [BLEUBERI: BLEU is a surprisingly effective reward for instruction following](https://arxiv.org/abs/2505.11080) *— 2025 · arXiv:2505.11080*
10. [From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge](https://aclanthology.org/2025.emnlp-main.138/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
11. [Investigating Length Issues in Document-level Machine Translation](https://aclanthology.org/2025.mtsummit-1.3/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
12. [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*
13. [References Matter: Investigating the Impact of Reference Set Variation on Summarization Evaluation](https://aclanthology.org/2025.inlg-main.18/) *— 2025 · Proceedings of the 18th International Natural Language Generation Conference*
14. [ReproHum \#0031-01: Reproducing the Human Evaluation of Readability from ``It is AI''s Turn to Ask Humans a Question](https://aclanthology.org/2025.gem-1.52/) *— 2025 · Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM\texttwosuperior)*
15. [Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability](https://aclanthology.org/2025.acl-long.1508/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
16. [The Good, the Bad and the Constructive: Automatically Measuring Peer Review''s Utility for Authors](https://aclanthology.org/2025.emnlp-main.1476/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
17. [What's the Difference? Supporting Users in Identifying the Effects of Prompt and Model Changes Through Token Patterns](https://aclanthology.org/2025.acl-long.985/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
18. [Évaluation de la Robustesse des LLM : Proposition d''un Cadre Méthodologique et Développement d''un Benchmark](https://aclanthology.org/2025.jeptalnrecital-evalllm.13/) *— 2025 · Actes de l'atelier Évaluation des modèles génératifs (LLM) et challenge 2025 (EvalLLM)*
19. [An Analysis on Automated Metrics for Evaluating Japanese-English Chat Translation](https://arxiv.org/abs/2412.18190) *— 2024 · arXiv:2412.18190*
20. [Automatic Metrics in Natural Language Generation: A survey of Current Evaluation Practices](https://aclanthology.org/2024.inlg-main.44/) *— 2024 · Proceedings of the 17th International Natural Language Generation Conference*
21. [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)*
22. [Cultural Adaptation of Recipes](https://aclanthology.org/2024.tacl-1.5/) *— 2024 · Transactions of the Association for Computational Linguistics*
23. [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)*
24. [From RAG to QA-RAG: Integrating Generative AI for Pharmaceutical Regulatory Compliance Process](https://arxiv.org/abs/2402.01717) *— 2024 · arXiv:2402.01717*
25. [Is Explanation All You Need? An Expert Survey on LLM-generated Explanations for Abusive Language Detection](https://aclanthology.org/2024.clicit-1.34/) *— 2024 · Proceedings of the Tenth Italian Conference on Computational Linguistics (CLiC-it 2024)*
26. [LARGEMED: A Resource for Identifying and Generating Paraphrases for French Medical Terms](https://aclanthology.org/2024.determit-1.14/) *— 2024 · Proceedings of the Workshop on DeTermIt! Evaluating Text Difficulty in a Multilingual Context @ LREC-COLING 2024*
27. [Low-Resource Machine Translation through Retrieval-Augmented LLM Prompting: A Study on the Mambai Language](https://arxiv.org/abs/2404.04809) *— 2024 · arXiv:2404.04809*
28. [METAL: Towards Multilingual Meta-Evaluation](https://aclanthology.org/2024.findings-naacl.148/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
29. [PoLLMgraph: Unraveling Hallucinations in Large Language Models via State Transition Dynamics](https://aclanthology.org/2024.findings-naacl.294/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
30. [Presence or Absence: Are Unknown Word Usages in Dictionaries?](https://aclanthology.org/2024.lchange-1.5/) *— 2024 · LChange 2024 (ACL workshop)*
31. [SedarEval: Automated Evaluation using Self-Adaptive Rubrics](https://aclanthology.org/2024.findings-emnlp.984/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
32. [Summarizing Long Regulatory Documents with a Multi-Step Pipeline](https://aclanthology.org/2024.nllp-1.2/) *— 2024 · Proceedings of the Natural Legal Language Processing Workshop 2024*
33. [À propos des difficultés de traduire automatiquement de longs documents](https://aclanthology.org/2024.jeptalnrecital-taln.1/) *— 2024 · Actes de la 31ème Conférence sur le Traitement Automatique des Langues Naturelles, volume 1 : articles longs et prises de position*
34. [Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?](https://arxiv.org/abs/2309.07462) *— 2023 · arXiv:2309.07462*
35. [BLEURT Has Universal Translations: An Analysis of Automatic Metrics by Minimum Risk Training](https://aclanthology.org/2023.acl-long.297/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
36. [ELQA: A Corpus of Metalinguistic Questions and Answers about English](https://aclanthology.org/2023.acl-long.113/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
37. [Evaluating Evaluation Metrics: A Framework for Analyzing NLG Evaluation Metrics using Measurement Theory](https://aclanthology.org/2023.emnlp-main.676/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
38. [GUMSum: Multi-Genre Data and Evaluation for English Abstractive Summarization](https://aclanthology.org/2023.findings-acl.593/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
39. [It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance](https://aclanthology.org/2023.findings-acl.202/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
40. [Learning Answer Generation using Supervision from Automatic Question Answering Evaluators](https://aclanthology.org/2023.acl-long.467/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
41. [Pulling Out All The Full Stops: Punctuation Sensitivity in Neural Machine Translation and Evaluation](https://aclanthology.org/2023.findings-acl.381/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
42. [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*
43. [The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation](https://aclanthology.org/2023.findings-emnlp.444/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
44. [Uniform Complexity for Text Generation](https://aclanthology.org/2023.findings-emnlp.805/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
45. [ALIGNMEET: A Comprehensive Tool for Meeting Annotation, Alignment, and Evaluation](https://aclanthology.org/2022.lrec-1.188/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
46. [Boosting Code Summarization by Embedding Code Structures](https://aclanthology.org/2022.coling-1.521/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
47. [Challenges and Strategies in Cross-Cultural NLP](https://aclanthology.org/2022.acl-long.482/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
48. [CodeExp: Explanatory Code Document Generation](https://aclanthology.org/2022.findings-emnlp.174/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
49. [Controlled Language Generation for Language Learning Items](https://aclanthology.org/2022.emnlp-industry.30/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track*
50. [Extended Parallel Corpus for Amharic-English Machine Translation](https://aclanthology.org/2022.lrec-1.716/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
51. [Generative Language Models for Paragraph-Level Question Generation](https://aclanthology.org/2022.emnlp-main.42/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
52. [How Do Seq2Seq Models Perform on End-to-End Data-to-Text Generation?](https://aclanthology.org/2022.acl-long.531/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
53. [NeuS: Neutral Multi-News Summarization for Mitigating Framing Bias](https://aclanthology.org/2022.naacl-main.228/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
54. [Quantifying Bias from Decoding Techniques in Natural Language Generation](https://aclanthology.org/2022.coling-1.112/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
55. [Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text](https://arxiv.org/abs/2202.06935) *— 2022 · arXiv:2202.06935*
56. [Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling](https://aclanthology.org/2022.acl-long.418/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
57. [Speech-to-Text and Evaluation of Multiple Machine Translation Systems](https://aclanthology.org/2022.amta-upg.33/) *— 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)*
58. [Survey of Hallucination in Natural Language Generation](https://arxiv.org/abs/2202.03629) *— 2022 · arXiv:2202.03629 · ACM Computing Surveys (2022)*
59. [TYPIC: A Corpus of Template-Based Diagnostic Comments on Argumentation](https://aclanthology.org/2022.lrec-1.636/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
60. [The Human Evaluation Datasheet: A Template for Recording Details of Human Evaluation Experiments in NLP](https://aclanthology.org/2022.humeval-1.6/) *— 2022 · Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)*
61. [TopKG: Target-oriented Dialog via Global Planning on Knowledge Graph](https://aclanthology.org/2022.coling-1.62/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
62. [WDV: A Broad Data Verbalisation Dataset Built from Wikidata](https://arxiv.org/abs/2205.02627) *— 2022 · arXiv:2205.02627*
63. [A Comprehensive Assessment of Dialog Evaluation Metrics](https://aclanthology.org/2021.eancs-1.3/) *— 2021 · The First Workshop on Evaluations and Assessments of Neural Conversation Systems*
64. [A Systematic Review of Reproducibility Research in Natural Language Processing](https://aclanthology.org/2021.eacl-main.29/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
65. [An Error Analysis Framework for Shallow Surface Realization](https://md.mova.elamur.ai/free/en/docs/papers/shimorina-2021-error-analysis-framework-shallow-surface/) *— our card · 2021*
66. [BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-Oriented Text](https://aclanthology.org/2021.triton-1.6/) *— 2021 · Proceedings of the Translation and Interpreting Technology Online Conference*
67. [Building Adaptive Acceptability Classifiers for Neural NLG](https://aclanthology.org/2021.emnlp-main.53/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
68. [Building and Evaluating Open-Domain Dialogue Corpora with Clarifying Questions](https://aclanthology.org/2021.emnlp-main.367/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
69. [Do Context-Aware Translation Models Pay the Right Attention?](https://aclanthology.org/2021.acl-long.65/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
70. [Exploring Metaphoric Paraphrase Generation](https://aclanthology.org/2021.conll-1.26/) *— 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
71. [Improving Unsupervised Question Answering via Summarization-Informed Question Generation](https://aclanthology.org/2021.emnlp-main.340/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
72. [Naturalness Evaluation of Natural Language Generation in Task-oriented Dialogues Using BERT](https://aclanthology.org/2021.ranlp-1.96/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
73. [OTTers: One-turn Topic Transitions for Open-Domain Dialogue](https://aclanthology.org/2021.acl-long.194/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
74. [On the Need for Thoughtful Data Collection for Multi-Party Dialogue: A Survey of Available Corpora and Collection Methods](https://aclanthology.org/2021.sigdial-1.36/) *— 2021 · Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue*
75. [Perturbation CheckLists for Evaluating NLG Evaluation Metrics](https://aclanthology.org/2021.emnlp-main.575/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
76. [Preregistering NLP research](https://aclanthology.org/2021.naacl-main.51/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
77. [Reliability Testing for Natural Language Processing Systems](https://aclanthology.org/2021.acl-long.321/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
78. [Rethinking Coherence Modeling: Synthetic vs. Downstream Tasks](https://aclanthology.org/2021.eacl-main.308/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
79. [Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers](https://aclanthology.org/2021.acl-long.566/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
80. [Sentiment-Aware Measure (SAM) for Evaluating Sentiment Transfer by Machine Translation Systems](https://aclanthology.org/2021.ranlp-1.137/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
81. [The (Un)Suitability of Automatic Evaluation Metrics for Text Simplification](https://aclanthology.org/2021.cl-4.28/) *— 2021 · Computational Linguistics*
82. [The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics](https://aclanthology.org/2021.gem-1.10/) *— 2021 · Proceedings of the First Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
83. [The Great Misalignment Problem in Human Evaluation of NLP Methods](https://aclanthology.org/2021.humeval-1.8/) *— 2021 · Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)*
84. [The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation](https://aclanthology.org/2021.emnlp-main.97/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
85. [The ReproGen Shared Task on Reproducibility of Human Evaluations in NLG: Overview and Results](https://aclanthology.org/2021.inlg-1.24/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
86. [The statistical advantage of automatic NLG metrics at the system level](https://aclanthology.org/2021.acl-long.533/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
87. [To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation](https://aclanthology.org/2021.wmt-1.57/) *— 2021 · Proceedings of the Sixth Conference on Machine Translation*
88. [Trainable Ranking Models to Evaluate the Semantic Accuracy of Data-to-Text Neural Generator](https://aclanthology.org/2021.eval4nlp-1.6/) *— 2021 · Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems*
89. [Underreporting of errors in NLG output, and what to do about it](https://aclanthology.org/2021.inlg-1.14/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
90. [A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systems](https://aclanthology.org/2020.inlg-1.22/) *— 2020 · Proceedings of the 13th International Conference on Natural Language Generation*
91. [A Human Evaluation of AMR-to-English Generation Systems](https://md.mova.elamur.ai/free/en/docs/papers/manning-2020-human-evaluation-amr-english-generation/) *— our card · 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
92. [Best Practices for Crowd-based Evaluation of German Summarization: Comparing Crowd, Expert and Automatic Evaluation](https://aclanthology.org/2020.eval4nlp-1.16/) *— 2020 · Proceedings of the First Workshop on Evaluation and Comparison of NLP Systems*
93. [Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data](https://aclanthology.org/2020.findings-emnlp.76/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
94. [Data-Driven Sentence Simplification: Survey and Benchmark](https://aclanthology.org/2020.cl-1.4/) *— 2020 · Computational Linguistics*
95. [Disentangling the Properties of Human Evaluation Methods: A Classification System to Support Comparability, Meta-Evaluation and Reproducibility Testing](https://aclanthology.org/2020.inlg-1.24/) *— 2020 · Proceedings of the 13th International Conference on Natural Language Generation*
96. [Evaluation of Text Generation: A Survey](https://arxiv.org/abs/2006.14799) *— 2020 · arXiv:2006.14799*
97. [Gradations of Error Severity in Automatic Image Descriptions](https://aclanthology.org/2020.inlg-1.45/) *— 2020 · Proceedings of the 13th International Conference on Natural Language Generation*
98. [History for Visual Dialog: Do we really need it?](https://aclanthology.org/2020.acl-main.728/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
99. [NUBIA: NeUral Based Interchangeability Assessor for Text Generation](https://aclanthology.org/2020.evalnlgeval-1.4/) *— 2020 · Proceedings of the 1st Workshop on Evaluating NLG Evaluation*
100. [On the interaction of automatic evaluation and task framing in headline style transfer](https://aclanthology.org/2020.evalnlgeval-1.5/) *— 2020 · Proceedings of the 1st Workshop on Evaluating NLG Evaluation*

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