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# Who cites «Bleu: a Method for Automatic Evaluation of Machine Translation» · page 28

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](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-7/) · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/papineni-2002-bleu-method-automatic-evaluation-machine-8/) · 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6. [Analyzing Dynamic Adversarial Training Data in the Limit](https://aclanthology.org/2022.findings-acl.18/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
7. [Analyzing Multi-Task Learning for Abstractive Text Summarization](https://aclanthology.org/2022.gem-1.5/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
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38. [Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand](https://aclanthology.org/2022.naacl-main.259/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
39. [Bilingual Tabular Inference: A Case Study on Indic Languages](https://aclanthology.org/2022.naacl-main.295/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
40. [BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model](https://aclanthology.org/2022.bionlp-1.9/) *— 2022 · Proceedings of the 21st Workshop on Biomedical Language Processing*
41. [BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://aclanthology.org/2022.naacl-main.111/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
42. [Boosting Code Summarization by Embedding Code Structures](https://aclanthology.org/2022.coling-1.521/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
43. [Breaking Down Multilingual Machine Translation](https://aclanthology.org/2022.findings-acl.218/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
44. [Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation](https://aclanthology.org/2022.acl-long.456/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [Bridging the Gap between Training and Inference: Multi-Candidate Optimization for Diverse Neural Machine Translation](https://aclanthology.org/2022.findings-naacl.200/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
46. [CARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generation](https://aclanthology.org/2022.findings-emnlp.51/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
47. [CDialog: A Multi-turn Covid-19 Conversation Dataset for Entity-Aware Dialog Generation](https://aclanthology.org/2022.emnlp-main.782/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
48. [CHAE: Fine-Grained Controllable Story Generation with Characters, Actions and Emotions](https://aclanthology.org/2022.coling-1.559/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
49. [CHIA: CHoosing Instances to Annotate for Machine Translation](https://aclanthology.org/2022.findings-emnlp.540/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
50. [CICERO: A Dataset for Contextualized Commonsense Inference in Dialogues](https://aclanthology.org/2022.acl-long.344/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
51. [CLIP4IDC: CLIP for Image Difference Captioning](https://aclanthology.org/2022.aacl-short.5/) *— 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
52. [CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers](https://aclanthology.org/2022.coling-1.146/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
53. [COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task](https://aclanthology.org/2022.wmt-1.52/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
54. [COMET-QE and Active Learning for Low-Resource Machine Translation](https://aclanthology.org/2022.findings-emnlp.348/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
55. [COMMA: Modeling Relationship among Motivations, Emotions and Actions in Language-based Human Activities](https://aclanthology.org/2022.coling-1.15/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
56. [COMPILING: A Benchmark Dataset for Chinese Complexity Controllable Definition Generation](https://aclanthology.org/2022.ccl-1.81/) *— 2022 · Proceedings of the 21st Chinese National Conference on Computational Linguistics*
57. [CQG: A Simple and Effective Controlled Generation Framework for Multi-hop Question Generation](https://aclanthology.org/2022.acl-long.475/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
58. [CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation](https://aclanthology.org/2022.acl-long.164/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
59. [CUNI-KIT System for Simultaneous Speech Translation Task at IWSLT 2022](https://aclanthology.org/2022.iwslt-1.24/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
60. [CURIE: An Iterative Querying Approach for Reasoning About Situations](https://aclanthology.org/2022.csrr-1.7/) *— 2022 · Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022)*
61. [CVSS Corpus and Massively Multilingual Speech-to-Speech Translation](https://aclanthology.org/2022.lrec-1.720/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
62. [Can NMT Understand Me? Towards Perturbation-based Evaluation of NMT Models for Code Generation](https://arxiv.org/abs/2203.15319) *— 2022 · arXiv:2203.15319*
63. [Can Pretrained Language Models Generate Persuasive, Faithful, and Informative Ad Text for Product Descriptions?](https://aclanthology.org/2022.ecnlp-1.27/) *— 2022 · Proceedings of the Fifth Workshop on e-Commerce and NLP (ECNLP 5)*
64. [Can Synthetic Translations Improve Bitext Quality?](https://aclanthology.org/2022.acl-long.326/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
65. [Can We Use Word Embeddings for Enhancing Guarani-Spanish Machine Translation?](https://aclanthology.org/2022.computel-1.16/) *— 2022 · Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages*
66. [Candidate Soups: Fusing Candidate Results Improves Translation Quality for Non-Autoregressive Translation](https://aclanthology.org/2022.emnlp-main.318/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
67. [Categorizing Semantic Representations for Neural Machine Translation](https://aclanthology.org/2022.coling-1.464/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
68. [Challenges of Neural Machine Translation for Short Texts](https://aclanthology.org/2022.cl-2.3/) *— 2022 · Computational Linguistics*
69. [Challenges with Sign Language Datasets for Sign Language Recognition and Translation](https://aclanthology.org/2022.lrec-1.264/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
70. [Chat Translation Error Detection for Assisting Cross-lingual Communications](https://aclanthology.org/2022.eval4nlp-1.9/) *— 2022 · Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems*
71. [ChatMatch: Evaluating Chatbots by Autonomous Chat Tournaments](https://aclanthology.org/2022.acl-long.522/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
72. [Chunk-based Nearest Neighbor Machine Translation](https://aclanthology.org/2022.emnlp-main.284/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
73. [CipherDAug: Ciphertext based Data Augmentation for Neural Machine Translation](https://aclanthology.org/2022.acl-long.17/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
74. [ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification](https://aclanthology.org/2022.acl-long.183/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
75. [Clean Text and Full-Body Transformer: Microsoft''s Submission to the WMT22 Shared Task on Sign Language Translation](https://aclanthology.org/2022.wmt-1.93/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
76. [Clickbait Spoiling via Question Answering and Passage Retrieval](https://aclanthology.org/2022.acl-long.484/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
77. [Cloze Evaluation for Deeper Understanding of Commonsense Stories in Indonesian](https://aclanthology.org/2022.csrr-1.2/) *— 2022 · Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022)*
78. [CoCoa: An Encoder-Decoder Model for Controllable Code-switched Generation](https://aclanthology.org/2022.emnlp-main.158/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
79. [CoDoNMT: Modeling Cohesion Devices for Document-Level Neural Machine Translation](https://aclanthology.org/2022.coling-1.462/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
80. [CoHS-CQG: Context and History Selection for Conversational Question Generation](https://aclanthology.org/2022.coling-1.48/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
81. [CoSe-Co: Text Conditioned Generative CommonSense Contextualizer](https://aclanthology.org/2022.naacl-main.83/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
82. [CodeExp: Explanatory Code Document Generation](https://aclanthology.org/2022.findings-emnlp.174/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
83. [CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning](https://arxiv.org/abs/2207.01780) *— 2022 · arXiv:2207.01780*
84. [CoditT5: Pretraining for Source Code and Natural Language Editing](https://arxiv.org/abs/2208.05446) *— 2022 · arXiv:2208.05446*
85. [Cognitive Simplification Operations Improve Text Simplification](https://aclanthology.org/2022.conll-1.17/) *— 2022 · Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)*
86. [Coherence boosting: When your pretrained language model is not paying enough attention](https://aclanthology.org/2022.acl-long.565/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
87. [ComFact: A Benchmark for Linking Contextual Commonsense Knowledge](https://aclanthology.org/2022.findings-emnlp.120/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
88. [Commonsense and Named Entity Aware Knowledge Grounded Dialogue Generation](https://aclanthology.org/2022.naacl-main.95/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
89. [Competency-Aware Neural Machine Translation: Can Machine Translation Know its Own Translation Quality?](https://aclanthology.org/2022.emnlp-main.330/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
90. [Complex Reading Comprehension Through Question Decomposition](https://aclanthology.org/2022.alta-1.5/) *— 2022 · Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association*
91. [Concadia: Towards Image-Based Text Generation with a Purpose](https://aclanthology.org/2022.emnlp-main.308/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
92. [Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation](https://aclanthology.org/2022.acl-long.206/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
93. [Consistent Human Evaluation of Machine Translation across Language Pairs](https://aclanthology.org/2022.amta-research.24/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
94. [Constrained Regeneration for Cross-Lingual Query-Focused Extractive Summarization](https://aclanthology.org/2022.coling-1.236/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
95. [Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation](https://aclanthology.org/2022.findings-emnlp.270/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
96. [Construction of a Quality Estimation Dataset for Automatic Evaluation of Japanese Grammatical Error Correction](https://aclanthology.org/2022.lrec-1.596/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
97. [Consultation Checklists: Standardising the Human Evaluation of Medical Note Generation](https://aclanthology.org/2022.emnlp-industry.10/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track*
98. [Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics](https://aclanthology.org/2022.emnlp-main.309/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
99. [Context-Aware Abbreviation Expansion Using Large Language Models](https://aclanthology.org/2022.naacl-main.91/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
100. [Context-Tuning: Learning Contextualized Prompts for Natural Language Generation](https://aclanthology.org/2022.coling-1.552/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*

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