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# Who cites «Bleu: a Method for Automatic Evaluation of Machine Translation» · page 7

10821 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/papineni-2002-bleu-method-automatic-evaluation-machine/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-6/) · **7** · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-9/) · 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33. [FormalMATH: Benchmarking Formal Mathematical Reasoning of Large Language Models](https://arxiv.org/abs/2505.02735) *— 2025 · arXiv:2505.02735*
34. [FormosanBench: Benchmarking Low-Resource Austronesian Languages in the Era of Large Language Models](https://aclanthology.org/2025.findings-emnlp.897/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
35. [Found in Translation: Measuring Multilingual LLM Consistency as Simple as Translate then Evaluate](https://aclanthology.org/2025.ijcnlp-long.185/) *— 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*
36. [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*
37. [From Heart to Words: Generating Empathetic Responses via Integrated Figurative Language and Semantic Context Signals](https://aclanthology.org/2025.findings-acl.231/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
38. [From Priest to Doctor: Domain Adaptation for Low-Resource Neural Machine Translation](https://aclanthology.org/2025.coling-main.472/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
39. [From Reasoning to Learning: A Survey on Hypothesis Discovery and Rule Learning with Large Language Models](https://arxiv.org/abs/2505.21935) *— 2025 · arXiv:2505.21935*
40. [From SALAMANDRA to SALAMANDRATA: BSC Submission for WMT25 General Machine Translation Shared Task](https://aclanthology.org/2025.wmt-1.37/) *— 2025 · Proceedings of the Tenth Conference on Machine Translation*
41. [From Scratch to Fine-Tuned: A Comparative Study of Transformer Training Strategies for Legal Machine Translation](https://aclanthology.org/2025.justnlp-main.20/) *— 2025 · Proceedings of the 1st Workshop on NLP for Empowering Justice (JUST-NLP 2025)*
42. [From Superficial to Deep: Integrating External Knowledge for Follow-up Question Generation Using Knowledge Graph and LLM](https://aclanthology.org/2025.coling-main.55/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
43. [From Text to Multi-Modal: Advancing Low-Resource-Language Translation through Synthetic Data Generation and Cross-Modal Alignments](https://aclanthology.org/2025.loresmt-1.4/) *— 2025 · Proceedings of the Eighth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2025)*
44. [From Tower to Spire: Adding the Speech Modality to a Translation-Specialist LLM](https://aclanthology.org/2025.findings-emnlp.1071/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
45. [G2: Guided Generation for Enhanced Output Diversity in LLMs](https://aclanthology.org/2025.emnlp-main.713/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
46. [GENDEROUS: Machine Translation and Cross-Linguistic Evaluation of a Gender-Ambiguous Dataset](https://aclanthology.org/2025.gebnlp-1.27/) *— 2025 · Proceedings of the 6th Workshop on Gender Bias in Natural Language Processing (GeBNLP)*
47. [GRAMMAR-LLM: Grammar-Constrained Natural Language Generation](https://aclanthology.org/2025.findings-acl.177/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
48. [GeNRe: A French Gender-Neutral Rewriting System Using Collective Nouns](https://aclanthology.org/2025.findings-acl.411/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
49. [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)*
50. [Gender Swapping as a Data Augmentation Technique: Developing Gender-Balanced Datasets for Ukrainian Language Processing](https://aclanthology.org/2025.unlp-1.16/) *— 2025 · Proceedings of the Fourth Ukrainian Natural Language Processing Workshop (UNLP 2025)*
51. [Gender-Neutral Rewriting in Italian: Models, Approaches, and Trade-offs](https://aclanthology.org/2025.clicit-1.84/) *— 2025 · Proceedings of the Eleventh Italian Conference on Computational Linguistics (CLiC-it 2025)*
52. [Generalized Tree Edit Distance (GTED): A Faithful Evaluation Metric for Statement Autoformalization](https://arxiv.org/abs/2507.07399) *— 2025 · arXiv:2507.07399*
53. [Generating and Evaluating Multi-Level Text Simplification: A Case Study on Italian](https://aclanthology.org/2025.clicit-1.82/) *— 2025 · Proceedings of the Eleventh Italian Conference on Computational Linguistics (CLiC-it 2025)*
54. [German4All – A Dataset and Model for Readability-Controlled Paraphrasing in German](https://aclanthology.org/2025.inlg-main.24/) *— 2025 · Proceedings of the 18th International Natural Language Generation Conference*
55. [Giving the Old a Fresh Spin: Quality Estimation-Assisted Constrained Decoding for Automatic Post-Editing](https://aclanthology.org/2025.naacl-short.77/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)*
56. [Going Beyond Your Expectations in Latency Metrics for Simultaneous Speech Translation](https://aclanthology.org/2025.findings-acl.937/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
57. [Graders Should Cheat: Privileged Information Enables Expert-Level Automated Evaluations](https://aclanthology.org/2025.emnlp-main.838/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
58. [GrammaMT: Improving Machine Translation with Grammar-Informed In-Context Learning](https://aclanthology.org/2025.acl-long.1447/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
59. [Group-Aware Reinforcement Learning for Output Diversity in Large Language Models](https://aclanthology.org/2025.emnlp-main.1649/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
60. [GuRE:Generative Query REwriter for Legal Passage Retrieval](https://aclanthology.org/2025.nllp-1.31/) *— 2025 · Proceedings of the Natural Legal Language Processing Workshop 2025*
61. [Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agents](https://aclanthology.org/2025.findings-emnlp.819/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
62. [HPSS: Heuristic Prompting Strategy Search for LLM Evaluators](https://aclanthology.org/2025.findings-acl.1282/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
63. [Harmonizing Diverse Models: A Layer-wise Merging Strategy for Consistent Generation](https://aclanthology.org/2025.emnlp-industry.64/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track*
64. [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)*
65. [Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies](https://aclanthology.org/2025.naacl-long.379/) *— 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)*
66. [Hello Again! LLM-powered Personalized Agent for Long-term Dialogue](https://aclanthology.org/2025.naacl-long.272/) *— 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)*
67. [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*
68. [HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights](https://arxiv.org/abs/2505.04846) *— 2025 · arXiv:2505.04846*
69. [Hierarchical Long-Document Summarization using LED for Legal Judgments](https://aclanthology.org/2025.justnlp-main.22/) *— 2025 · Proceedings of the 1st Workshop on NLP for Empowering Justice (JUST-NLP 2025)*
70. [How Far Are AI Scientists from Changing the World?](https://arxiv.org/abs/2507.23276) *— 2025 · arXiv:2507.23276*
71. [How Real Are Synthetic Therapy Conversations? Evaluating Fidelity in Prolonged Exposure Dialogues](https://aclanthology.org/2025.findings-emnlp.1144/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
72. [How Reliable is Multilingual LLM-as-a-Judge?](https://aclanthology.org/2025.findings-emnlp.587/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
73. [How Small Can You Go? Compact Language Models for On-Device Critical Error Detection in Machine Translation](https://arxiv.org/abs/2511.09748) *— 2025 · arXiv:2511.09748*
74. [How Well Can Large Language Models Reflect? A Human Evaluation of LLM-generated Reflections for Motivational Interviewing Dialogues](https://aclanthology.org/2025.coling-main.135/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
75. [How Well Do LLMs Handle Cantonese? Benchmarking Cantonese Capabilities of Large Language Models](https://aclanthology.org/2025.findings-naacl.253/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
76. [How Well Do LLMs Understand Tunisian Arabic?](https://arxiv.org/abs/2511.16683) *— 2025 · arXiv:2511.16683*
77. [How ``Real'' is Your Real-Time Simultaneous Speech-to-Text Translation System?](https://aclanthology.org/2025.tacl-1.14/) *— 2025 · Transactions of the Association for Computational Linguistics*
78. [How to Evaluate Speech Translation with Source-Aware Neural MT Metrics](https://arxiv.org/abs/2511.03295) *— 2025 · arXiv:2511.03295*
79. [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*
80. [Hunyuan-MT Technical Report](https://arxiv.org/abs/2509.05209) *— 2025 · arXiv:2509.05209*
81. [IHEval: Evaluating Language Models on Following the Instruction Hierarchy](https://aclanthology.org/2025.naacl-long.425/) *— 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)*
82. [IRR: Image Review Ranking Framework for Evaluating Vision-Language Models](https://aclanthology.org/2025.coling-main.665/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
83. [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*
84. [Identifying Reliable Evaluation Metrics for Scientific Text Revision](https://aclanthology.org/2025.acl-long.335/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
85. [ImageEval 2025: The First Arabic Image Captioning Shared Task](https://aclanthology.org/2025.arabicnlp-sharedtasks.52/) *— 2025 · Proceedings of The Third Arabic Natural Language Processing Conference: Shared Tasks*
86. [ImgTrojan: Jailbreaking Vision-Language Models with ONE Image](https://aclanthology.org/2025.naacl-long.360/) *— 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)*
87. [Implementing Long Text Style Transfer with LLMs through Dual-Layered Sentence and Paragraph Structure Extraction and Mapping](https://arxiv.org/abs/2505.07888) *— 2025 · arXiv:2505.07888*
88. [Improving Estonian Text Simplification through Pretrained Language Models and Custom Datasets](https://aclanthology.org/2025.ranlp-1.16/) *— 2025 · Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era*
89. [Improving Text Style Transfer using Masked Diffusion Language Models with Inference-time Scaling](https://arxiv.org/abs/2508.10995) *— 2025 · arXiv:2508.10995*
90. [In-Context Example Selection via Similarity Search Improves Low-Resource Machine Translation](https://aclanthology.org/2025.findings-naacl.68/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
91. [InImageTrans: Multimodal LLM-based Text Image Machine Translation](https://aclanthology.org/2025.findings-acl.1039/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
92. [Inductive Linguistic Reasoning with Large Language Models](https://aclanthology.org/2025.findings-acl.1171/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
93. [InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery](https://aclanthology.org/2025.coling-main.25/) *— 2025 · Proceedings of the 31st International Conference on Computational Linguistics*
94. [Instruction-tuned Large Language Models for Machine Translation in the Medical Domain](https://aclanthology.org/2025.mtsummit-1.13/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
95. [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*
96. [Introducing Quality Estimation to Machine Translation Post-editing Workflow: An Empirical Study on Its Usefulness](https://aclanthology.org/2025.mtsummit-1.38/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
97. [Investigating Length Issues in Document-level Machine Translation](https://aclanthology.org/2025.mtsummit-1.3/) *— 2025 · Proceedings of Machine Translation Summit XX: Volume 1*
98. [Investigating the Effect of Backtranslation for Indic Languages](https://aclanthology.org/2025.indonlp-1.18/) *— 2025 · Proceedings of the First Workshop on Natural Language Processing for Indo-Aryan and Dravidian Languages*
99. [Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models](https://aclanthology.org/2025.naacl-long.485/) *— 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)*
100. [Isolating LLM Performance Gains in Pre-training versus Instruction-tuning for Mid-resource Languages: The Ukrainian Benchmark Study](https://aclanthology.org/2025.ranlp-1.100/) *— 2025 · Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era*

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