---
title: "Who cites Bleu: a Method for Automatic Evaluation of…"
description: "The papers of the Elamur Research library that cite «Bleu: a Method for Automatic Evaluation of Machine Translation», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/47/"
---
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# Who cites «Bleu: a Method for Automatic Evaluation of Machine Translation» · page 47

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

Pages: [1](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/) · … · [46](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/46/) · **47** · [48](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/48/) · … · [109](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/109/)

1. [Data Cartography for Low-Resource Neural Machine Translation](https://aclanthology.org/2022.findings-emnlp.410/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
2. [Data-Efficient Concept Extraction from Pre-trained Language Models for Commonsense Explanation Generation](https://aclanthology.org/2022.findings-emnlp.433/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
3. [Data-to-text Generation with Variational Sequential Planning](https://aclanthology.org/2022.tacl-1.40/) *— 2022 · Transactions of the Association for Computational Linguistics*
4. [DataLab: A Platform for Data Analysis and Intervention](https://aclanthology.org/2022.acl-demo.18/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations*
5. [Debiasing Event Understanding for Visual Commonsense Tasks](https://aclanthology.org/2022.findings-acl.65/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
6. [Deep Learning for Text Style Transfer: A Survey](https://aclanthology.org/2022.cl-1.6/) *— 2022 · Computational Linguistics*
7. [DeltaNet: Conditional Medical Report Generation for COVID-19 Diagnosis](https://aclanthology.org/2022.coling-1.261/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
8. [Dependency-based Mixture Language Models](https://aclanthology.org/2022.acl-long.535/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
9. [Detecting Unintended Social Bias in Toxic Language Datasets](https://aclanthology.org/2022.conll-1.10/) *— 2022 · Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)*
10. [Developing Machine Translation Engines for Multilingual Participatory Spaces](https://aclanthology.org/2022.eamt-1.69/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
11. [DialSummEval: Revisiting Summarization Evaluation for Dialogues](https://aclanthology.org/2022.naacl-main.418/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
12. [DialoKG: Knowledge-Structure Aware Task-Oriented Dialogue Generation](https://aclanthology.org/2022.findings-naacl.195/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
13. [DialogUSR: Complex Dialogue Utterance Splitting and Reformulation for Multiple Intent Detection](https://aclanthology.org/2022.findings-emnlp.234/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
14. [Dialogue Summaries as Dialogue States (DS2), Template-Guided Summarization for Few-shot Dialogue State Tracking](https://aclanthology.org/2022.findings-acl.302/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
15. [DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models](https://arxiv.org/abs/2210.08933) *— 2022 · arXiv:2210.08933*
16. [Diformer: Directional Transformer for Neural Machine Translation](https://aclanthology.org/2022.eamt-1.11/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
17. [Digging Errors in NMT: Evaluating and Understanding Model Errors from Partial Hypothesis Space](https://aclanthology.org/2022.emnlp-main.827/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
18. [Discourse Cohesion Evaluation for Document-Level Neural Machine Translation](https://arxiv.org/abs/2208.09118) *— 2022 · arXiv:2208.09118*
19. [Discourse-Aware Soft Prompting for Text Generation](https://aclanthology.org/2022.emnlp-main.303/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
20. [Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation](https://aclanthology.org/2022.emnlp-main.354/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
21. [Disentangled Variational Topic Inference for Topic-Accurate Financial Report Generation](https://aclanthology.org/2022.finnlp-1.3/) *— 2022 · Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)*
22. [Disentangling Uncertainty in Machine Translation Evaluation](https://aclanthology.org/2022.emnlp-main.591/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
23. [Distill The Image to Nowhere: Inversion Knowledge Distillation for Multimodal Machine Translation](https://aclanthology.org/2022.emnlp-main.152/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
24. [Ditch the Gold Standard: Re-evaluating Conversational Question Answering](https://aclanthology.org/2022.acl-long.555/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
25. [DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages](https://aclanthology.org/2022.emnlp-main.532/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
26. [Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts](https://aclanthology.org/2022.findings-acl.149/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
27. [Diversifying Neural Text Generation with Part-of-Speech Guided Softmax and Sampling](https://aclanthology.org/2022.coling-1.570/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
28. [Divide and Conquer: Text Semantic Matching with Disentangled Keywords and Intents](https://aclanthology.org/2022.findings-acl.287/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
29. [Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models](https://aclanthology.org/2022.acl-long.312/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Do Decoding Algorithms Capture Discourse Structure in Multi-Modal Tasks? A Case Study of Image Paragraph Generation](https://aclanthology.org/2022.gem-1.45/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
31. [Doc2Bot: Accessing Heterogeneous Documents via Conversational Bots](https://aclanthology.org/2022.findings-emnlp.131/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
32. [Does Summary Evaluation Survive Translation to Other Languages?](https://aclanthology.org/2022.naacl-main.173/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
33. [Domain Adaptation in Neural Machine Translation using a Qualia-Enriched FrameNet](https://aclanthology.org/2022.lrec-1.1/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
34. [Domain Adaptation of Machine Translation with Crowdworkers](https://aclanthology.org/2022.emnlp-industry.62/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track*
35. [Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization](https://aclanthology.org/2022.cl-2.2/) *— 2022 · Computational Linguistics*
36. [Domain Curricula for Code-Switched MT at MixMT 2022](https://aclanthology.org/2022.wmt-1.117/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
37. [Domain-Specific Text Generation for Machine Translation](https://aclanthology.org/2022.amta-research.2/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
38. [Don”t Take It Literally: An Edit-Invariant Sequence Loss for Text Generation](https://aclanthology.org/2022.naacl-main.150/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
39. [Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation](https://aclanthology.org/2022.amta-research.12/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
40. [Dynamic Human Evaluation for Relative Model Comparisons](https://aclanthology.org/2022.lrec-1.639/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
41. [Dynamic Position Encoding for Transformers](https://aclanthology.org/2022.coling-1.450/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
42. [Décodage guidé par un discriminateur avec le Monte Carlo Tree Search pour la génération de texte contrainte (Discriminator-guided decoding with Monte Carlo Tree Search for constrained text generation )](https://aclanthology.org/2022.jeptalnrecital-taln.3/) *— 2022 · Actes de la 29e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale*
43. [EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multi-lingual Neural Machine Translation](https://aclanthology.org/2022.acl-long.560/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
44. [ELF22: A Context-based Counter Trolling Dataset to Combat Internet Trolls](https://aclanthology.org/2022.lrec-1.378/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
45. [ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text Generation](https://aclanthology.org/2022.emnlp-main.68/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
46. [EPT-X: An Expression-Pointer Transformer model that generates eXplanations for numbers](https://aclanthology.org/2022.acl-long.305/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
47. [ET5: A Novel End-to-end Framework for Conversational Machine Reading Comprehension](https://aclanthology.org/2022.coling-1.47/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
48. [Edinburgh at SemEval-2022 Task 1: Jointly Fishing for Word Embeddings and Definitions](https://aclanthology.org/2022.semeval-1.8/) *— 2022 · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)*
49. [Effective Unsupervised Constrained Text Generation based on Perturbed Masking](https://aclanthology.org/2022.findings-acl.111/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
50. [Efficient Constituency Tree based Encoding for Natural Language to Bash Translation](https://aclanthology.org/2022.naacl-main.230/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
51. [Efficient Task-Oriented Dialogue Systems with Response Selection as an Auxiliary Task](https://aclanthology.org/2022.icnlsp-1.2/) *— 2022 · Proceedings of the 5th International Conference on Natural Language and Speech Processing (ICNLSP 2022)*
52. [ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models](https://aclanthology.org/2022.naacl-main.258/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
53. [Emergent Abilities of Large Language Models](https://arxiv.org/abs/2206.07682) *— 2022 · arXiv:2206.07682*
54. [EmpHi: Generating Empathetic Responses with Human-like Intents](https://aclanthology.org/2022.naacl-main.78/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
55. [Empathetic Dialogue Generation via Sensitive Emotion Recognition and Sensible Knowledge Selection](https://aclanthology.org/2022.findings-emnlp.340/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
56. [Empathetic and Emotionally Positive Conversation Systems with an Emotion-specific Query-Response Memory](https://aclanthology.org/2022.findings-emnlp.475/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
57. [Empirical Evaluation of Language Agnostic Filtering of Parallel Data for Low Resource Languages](https://aclanthology.org/2022.paclic-1.38/) *— 2022 · Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation*
58. [Empowering parameter-efficient transfer learning by recognizing the kernel structure in self-attention](https://aclanthology.org/2022.findings-naacl.102/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
59. [Enabling arbitrary translation objectives with Adaptive Tree Search](https://arxiv.org/abs/2202.11444) *— 2022 · arXiv:2202.11444*
60. [End-to-end Dense Video Captioning as Sequence Generation](https://aclanthology.org/2022.coling-1.498/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
61. [English to Bengali Multimodal Neural Machine Translation using Transliteration-based Phrase Pairs Augmentation](https://aclanthology.org/2022.wat-1.14/) *— 2022 · Proceedings of the 9th Workshop on Asian Translation*
62. [English-Russian Data Augmentation for Neural Machine Translation](https://aclanthology.org/2022.amta-coco4mt.1/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Workshop 2: Corpus Generation and Corpus Augmentation for Machine Translation)*
63. [Enhancing Pre-trained Models with Text Structure Knowledge for Question Generation](https://aclanthology.org/2022.coling-1.571/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
64. [Enhancing the Transformer Decoder with Transition-based Syntax](https://aclanthology.org/2022.conll-1.27/) *— 2022 · Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)*
65. [Enriching Grammatical Error Correction Resources for Modern Greek](https://aclanthology.org/2022.lrec-1.532/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
66. [Entailment Relation Aware Paraphrase Generation](https://arxiv.org/abs/2203.10483) *— 2022 · arXiv:2203.10483*
67. [Error Analysis of ToTTo Table-to-Text Neural NLG Models](https://aclanthology.org/2022.gem-1.43/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
68. [EtriCA: Event-Triggered Context-Aware Story Generation Augmented by Cross Attention](https://aclanthology.org/2022.findings-emnlp.403/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
69. [Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention](https://aclanthology.org/2022.emnlp-main.745/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
70. [Evaluate & Evaluation on the Hub: Better Best Practices for Data and Model Measurements](https://aclanthology.org/2022.emnlp-demos.13/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
71. [Evaluating Agent Interactions Through Episodic Knowledge Graphs](https://aclanthology.org/2022.ccgpk-1.3/) *— 2022 · Proceedings of the 1st Workshop on Customized Chat Grounding Persona and Knowledge*
72. [Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark](https://aclanthology.org/2022.tacl-1.62/) *— 2022 · Transactions of the Association for Computational Linguistics*
73. [Evaluating Legal Accuracy of Neural Generators on the Generation of Criminal Court Dockets Description](https://aclanthology.org/2022.inlg-main.7/) *— 2022 · Proceedings of the 15th International Conference on Natural Language Generation*
74. [Evaluating MT Systems: A Theoretical Framework](https://arxiv.org/abs/2202.05806) *— 2022 · arXiv:2202.05806*
75. [Evaluating Machine Translation in Cross-lingual E-Commerce Search](https://aclanthology.org/2022.amta-research.25/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
76. [Evaluating Subtitle Segmentation for End-to-end Generation Systems](https://aclanthology.org/2022.lrec-1.328/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
77. [Evaluating the Examiner: The Perils of Pearson Correlation for Validating Text Similarity Metrics](https://aclanthology.org/2022.alta-1.18/) *— 2022 · Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association*
78. [Evaluating the Knowledge Dependency of Questions](https://aclanthology.org/2022.emnlp-main.718/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
79. [Evaluation of Automatic Text Simplification: Where are we now, where should we go from here](https://aclanthology.org/2022.jeptalnrecital-taln.47/) *— 2022 · Actes de la 29e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale*
80. [Evaluation of Response Generation Models: Shouldn”t It Be Shareable and Replicable?](https://aclanthology.org/2022.gem-1.12/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
81. [Evaluation of Transfer Learning for Polish with a Text-to-Text Model](https://aclanthology.org/2022.lrec-1.466/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
82. [Event Transition Planning for Open-ended Text Generation](https://aclanthology.org/2022.findings-acl.269/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
83. [ExPUNations: Augmenting Puns with Keywords and Explanations](https://aclanthology.org/2022.emnlp-main.304/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
84. [Examining Large Pre-Trained Language Models for Machine Translation: What You Don”t Know about It](https://aclanthology.org/2022.wmt-1.84/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
85. [Execution-based Evaluation for Data Science Code Generation Models](https://aclanthology.org/2022.dash-1.5/) *— 2022 · Proceedings of the Fourth Workshop on Data Science with Human-in-the-Loop (Language Advances)*
86. [Explaining Dialogue Evaluation Metrics using Adversarial Behavioral Analysis](https://aclanthology.org/2022.naacl-main.430/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
87. [Explaining Toxic Text via Knowledge Enhanced Text Generation](https://aclanthology.org/2022.naacl-main.59/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
88. [Explicit Use of Topicality in Dialogue Response Generation](https://aclanthology.org/2022.naacl-srw.28/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop*
89. [Exploiting Inductive Bias in Transformers for Unsupervised Disentanglement of Syntax and Semantics with VAEs](https://aclanthology.org/2022.naacl-main.423/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
90. [Explore More Guidance: A Task-aware Instruction Network for Sign Language Translation Enhanced with Data Augmentation](https://aclanthology.org/2022.findings-naacl.205/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
91. [Exploring Code Style Transfer with Neural Networks](https://arxiv.org/abs/2209.06273) *— 2022 · arXiv:2209.06273*
92. [Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature](https://aclanthology.org/2022.emnlp-main.672/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
93. [Exploring Robustness of Machine Translation Metrics: A Study of Twenty-Two Automatic Metrics in the WMT22 Metric Task](https://aclanthology.org/2022.wmt-1.46/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
94. [Exploring a POS-based Two-stage Approach for Improving Low-Resource AMR-to-Text Generation](https://aclanthology.org/2022.gem-1.49/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
95. [Exploring diversity in back translation for low-resource machine translation](https://aclanthology.org/2022.deeplo-1.8/) *— 2022 · Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing*
96. [Exploring the Benefits and Limitations of Multilinguality for Non-autoregressive Machine Translation](https://aclanthology.org/2022.wmt-1.11/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
97. [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*
98. [ExtraPhrase: Efficient Data Augmentation for Abstractive Summarization](https://aclanthology.org/2022.naacl-srw.3/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop*
99. [Extracting Latent Steering Vectors from Pretrained Language Models](https://aclanthology.org/2022.findings-acl.48/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
100. [FALTE: A Toolkit for Fine-grained Annotation for Long Text Evaluation](https://aclanthology.org/2022.emnlp-demos.35/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*

Pages: [1](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/) · … · [46](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/46/) · **47** · [48](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/48/) · … · [109](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/109/)