---
title: "Who cites A Structured Review of the Validity of BLEU"
description: "The papers of the Elamur Research library that cite «A Structured Review of the Validity of BLEU», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/reiter-2018-structured-review-validity-bleu/cited-by/"
---
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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.research.elamur.ai/free/en/papers/reiter-2018-structured-review-validity-bleu/)

Pages: **1** · [2](https://md.research.elamur.ai/free/en/papers/reiter-2018-structured-review-validity-bleu/cited-by/page/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. [Cross-Examination Framework: A Task-Agnostic Diagnostic for Information Fidelity in Text-to-Text Generation](https://aclanthology.org/2026.acl-long.1761/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [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*
4. [Evaluating Large Language Model-based Natural Language Generation for Modular Dialog systems](https://aclanthology.org/2026.resourceful-4.14/) *— 2026 · Proceedings of the Fourth Workshop on the Role of Resources in the Age of Large Language Models (RESOURCEFUL 2026)*
5. [Evaluating Task-oriented Dialogue Systems: A Systematic Review of Measures, Constructs and their Operationalisations](https://nejlt.ep.liu.se/article/view/5940) *— 2026 · Northern European Journal of Language Technology*
6. [JP-TL-Bench: Anchored Pairwise LLM Evaluation for Bidirectional Japanese-English Translation](https://arxiv.org/abs/2601.00223) *— 2026 · arXiv:2601.00223*
7. [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)*
8. [LLMs as Span Annotators: A Comparative Study of LLMs and Humans](https://aclanthology.org/2026.mme-main.1/) *— 2026 · Proceedings of the First Workshop on Multilingual Multicultural Evaluation*
9. [MATCHA: Matching Text via Contrastive Semantic Alignment](https://aclanthology.org/2026.findings-acl.1055/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026*
10. [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*
11. [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)*
12. [Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations](https://aclanthology.org/2026.gem-main.43/) *— 2026 · Proceedings of the Fifth Workshop on Generation, Evaluation and Metrics (GEM)*
13. [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*
14. [StoicLLM: Preference Optimization for Philosophical Alignment in Small Language Models](https://arxiv.org/abs/2605.11483) *— 2026 · arXiv:2605.11483*
15. [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*
16. [BLEUBERI: BLEU is a surprisingly effective reward for instruction following](https://arxiv.org/abs/2505.11080) *— 2025 · arXiv:2505.11080*
17. [CRScore: Grounding Automated Evaluation of Code Review Comments in Code Claims and Smells](https://aclanthology.org/2025.naacl-long.457/) *— 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)*
18. [Can LLMs Help Uncover Insights about LLMs? A Large-Scale, Evolving Literature Analysis of Frontier LLMs](https://aclanthology.org/2025.acl-long.998/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
19. [DCU-ADAPT-modPB at the GEM”24 Data-to-Text Task: Analysis of Human Evaluation Results](https://aclanthology.org/2025.inlg-genchal.3/) *— 2025 · Proceedings of the 18th International Natural Language Generation Conference: Generation Challenges*
20. [Do Large Language Models understand how to be judges?](https://aclanthology.org/2025.luhme-1.9/) *— 2025 · Proceedings of the 2nd LUHME Workshop*
21. [Do Robot Snakes Dream like Electric Sheep? Investigating the Effects of Architectural Inductive Biases on Hallucination](https://aclanthology.org/2025.findings-acl.60/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
22. [From Detection to Explanation: Effective Learning Strategies for LLMs in Online Abusive Language Research](https://aclanthology.org/2025.coling-main.141/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
23. [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*
24. [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*
25. [Implementing Retrieval Augmented Generation Technique on Unstructured and Structured Data Sources in a Call Center of a Large Financial Institution](https://aclanthology.org/2025.naacl-industry.48/) *— 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)*
26. [Investigating Length Issues in Document-level Machine Translation](https://aclanthology.org/2025.mtsummit-1.3/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
27. [MLLMs Construction Company: Investigating Multimodal LLMs” Communicative Skills in a Collaborative Building Task](https://aclanthology.org/2025.clicit-1.97/) *— 2025 · Proceedings of the Eleventh Italian Conference on Computational Linguistics (CLiC-it 2025)*
28. [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*
29. [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)*
30. [QuASAR: A Question-Driven Structure-Aware Approach for Table-to-Text Generation](https://aclanthology.org/2025.acl-long.1300/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
31. [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*
32. [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)*
33. [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)*
34. [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*
35. [Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems](https://aclanthology.org/2025.findings-acl.947/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
36. [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)*
37. [eC-Tab2Text: Aspect-Based Text Generation from e-Commerce Product Tables](https://aclanthology.org/2025.naacl-industry.65/) *— 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)*
38. [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)*
39. [An Analysis on Automated Metrics for Evaluating Japanese-English Chat Translation](https://arxiv.org/abs/2412.18190) *— 2024 · arXiv:2412.18190*
40. [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*
41. [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)*
42. [Context-aware Visual Storytelling with Visual Prefix Tuning and Contrastive Learning](https://aclanthology.org/2024.inlg-main.32/) *— 2024 · Proceedings of the 17th International Natural Language Generation Conference*
43. [Cultural Adaptation of Recipes](https://aclanthology.org/2024.tacl-1.5/) *— 2024 · Transactions of the Association for Computational Linguistics*
44. [Faithfulness of Natural Language Generation](https://aclanthology.org/2024.yrrsds-1.8/) *— 2024 · Proceedings of the 20th Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems*
45. [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)*
46. [From RAG to QA-RAG: Integrating Generative AI for Pharmaceutical Regulatory Compliance Process](https://arxiv.org/abs/2402.01717) *— 2024 · arXiv:2402.01717*
47. [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)*
48. [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*
49. [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*
50. [METAL: Towards Multilingual Meta-Evaluation](https://aclanthology.org/2024.findings-naacl.148/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
51. [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*
52. [Presence or Absence: Are Unknown Word Usages in Dictionaries?](https://aclanthology.org/2024.lchange-1.5/) *— 2024 · LChange 2024 (ACL workshop)*
53. [ReproHum \#0087-01: Human Evaluation Reproduction Report for Generating Fact Checking Explanations](https://aclanthology.org/2024.humeval-1.23/) *— 2024 · Proceedings of the Fourth Workshop on Human Evaluation of NLP Systems (HumEval) @ LREC-COLING 2024*
54. [ReproHum \#0927-3: Reproducing The Human Evaluation Of The DExperts Controlled Text Generation Method](https://aclanthology.org/2024.humeval-1.15/) *— 2024 · Proceedings of the Fourth Workshop on Human Evaluation of NLP Systems (HumEval) @ LREC-COLING 2024*
55. [SedarEval: Automated Evaluation using Self-Adaptive Rubrics](https://aclanthology.org/2024.findings-emnlp.984/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
56. [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*
57. [Tram: A Token-level Retrieval-augmented Mechanism for Source Code Summarization](https://aclanthology.org/2024.findings-naacl.186/) *— 2024 · Findings of the Association for Computational Linguistics: NAACL 2024*
58. [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*
59. [Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?](https://arxiv.org/abs/2309.07462) *— 2023 · arXiv:2309.07462*
60. [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)*
61. [Decomposed scoring of CCG dependencies](https://aclanthology.org/2023.acl-short.89/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
62. [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)*
63. [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*
64. [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*
65. [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*
66. [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)*
67. [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*
68. [SQUARE: Automatic Question Answering Evaluation using Multiple Positive and Negative References](https://aclanthology.org/2023.ijcnlp-short.3/) *— 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)*
69. [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*
70. [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*
71. [Uniform Complexity for Text Generation](https://aclanthology.org/2023.findings-emnlp.805/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
72. [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*
73. [Boosting Code Summarization by Embedding Code Structures](https://aclanthology.org/2022.coling-1.521/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
74. [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)*
75. [CodeExp: Explanatory Code Document Generation](https://aclanthology.org/2022.findings-emnlp.174/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
76. [Content Type Profiling of Data-to-Text Generation Datasets](https://aclanthology.org/2022.coling-1.507/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
77. [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*
78. [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*
79. [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*
80. [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)*
81. [Is NLP Ready for Standardization?](https://aclanthology.org/2022.findings-emnlp.202/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
82. [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*
83. [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*
84. [Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text](https://arxiv.org/abs/2202.06935) *— 2022 · arXiv:2202.06935*
85. [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)*
86. [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)*
87. [Survey of Hallucination in Natural Language Generation](https://arxiv.org/abs/2202.03629) *— 2022 · arXiv:2202.03629 · ACM Computing Surveys (2022)*
88. [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*
89. [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)*
90. [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*
91. [Universal Evasion Attacks on Summarization Scoring](https://aclanthology.org/2022.blackboxnlp-1.9/) *— 2022 · Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
92. [WDV: A Broad Data Verbalisation Dataset Built from Wikidata](https://arxiv.org/abs/2205.02627) *— 2022 · arXiv:2205.02627*
93. [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*
94. [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*
95. [An Error Analysis Framework for Shallow Surface Realization](https://md.research.elamur.ai/free/en/papers/shimorina-2021-error-analysis-framework-shallow-surface/) *— our card · 2021*
96. [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*
97. [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*
98. [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*
99. [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)*
100. [Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation](https://aclanthology.org/2021.humeval-1.2/) *— 2021 · Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)*

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