---
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/48/"
---
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# Who cites «Bleu: a Method for Automatic Evaluation of Machine Translation» · page 48

10827 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/) · … · [47](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/47/) · **48** · [49](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/49/) · … · [109](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/109/)

1. [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*
2. [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*
3. [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*
4. [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*
5. [FOAM: A Follower-aware Speaker Model For Vision-and-Language Navigation](https://aclanthology.org/2022.naacl-main.322/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
6. [FPI: Failure Point Isolation in Large-scale Conversational Assistants](https://aclanthology.org/2022.naacl-industry.17/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track*
7. [FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning](https://aclanthology.org/2022.emnlp-main.716/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
8. [Factual Accuracy is not Enough: Planning Consistent Description Order for Radiology Report Generation](https://aclanthology.org/2022.emnlp-main.480/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
9. [FaithDial: A Faithful Benchmark for Information-Seeking Dialogue](https://aclanthology.org/2022.tacl-1.84/) *— 2022 · Transactions of the Association for Computational Linguistics*
10. [FeatureBART: Feature Based Sequence-to-Sequence Pre-Training for Low-Resource NMT](https://aclanthology.org/2022.coling-1.443/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
11. [Feeding What You Need by Understanding What You Learned](https://aclanthology.org/2022.acl-long.403/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
12. [Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant Setup](https://aclanthology.org/2022.findings-emnlp.255/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
13. [Few-Shot Regularization to Tackle Catastrophic Forgetting in Multilingual Machine Translation](https://aclanthology.org/2022.amta-research.14/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
14. [Few-shot Table-to-text Generation with Prefix-Controlled Generator](https://aclanthology.org/2022.coling-1.565/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
15. [Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks](https://aclanthology.org/2022.findings-emnlp.378/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
16. [Findings of the 2022 Conference on Machine Translation (WMT22)](https://aclanthology.org/2022.wmt-1.1/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
17. [Findings of the First WMT Shared Task on Sign Language Translation (WMT-SLT22)](https://aclanthology.org/2022.wmt-1.71/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
18. [Findings of the IWSLT 2022 Evaluation Campaign](https://aclanthology.org/2022.iwslt-1.10/) *— 2022 · Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022)*
19. [Findings of the WMT 2022 Biomedical Translation Shared Task: Monolingual Clinical Case Reports](https://aclanthology.org/2022.wmt-1.69/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
20. [Findings of the WMT 2022 Shared Task on Automatic Post-Editing](https://aclanthology.org/2022.wmt-1.5/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
21. [Findings of the WMT 2022 Shared Task on Translation Suggestion](https://aclanthology.org/2022.wmt-1.76/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
22. [Fine-Grained Controllable Text Generation Using Non-Residual Prompting](https://aclanthology.org/2022.acl-long.471/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
23. [Fine-grained Contrastive Learning for Definition Generation](https://aclanthology.org/2022.aacl-main.73/) *— 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 1: Long Papers)*
24. [Fine-grained Image Captioning with CLIP Reward](https://aclanthology.org/2022.findings-naacl.39/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
25. [Fine-tuned Language Models are Continual Learners](https://arxiv.org/abs/2205.12393) *— 2022 · arXiv:2205.12393*
26. [FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation](https://aclanthology.org/2022.emnlp-main.220/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
27. [Flexible text generation for counterfactual fairness probing](https://aclanthology.org/2022.woah-1.20/) *— 2022 · Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH)*
28. [Flow-Adapter Architecture for Unsupervised Machine Translation](https://aclanthology.org/2022.acl-long.89/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
29. [FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows](https://aclanthology.org/2022.emnlp-main.715/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
30. [Focus! Relevant and Sufficient Context Selection for News Image Captioning](https://aclanthology.org/2022.findings-emnlp.450/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
31. [Focused Concatenation for Context-Aware Neural Machine Translation](https://aclanthology.org/2022.wmt-1.77/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
32. [Food for Thought: How can we exploit contextual embeddings in the translation of idiomatic expressions?](https://aclanthology.org/2022.flp-1.14/) *— 2022 · Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)*
33. [From COMET to COMES – Can Summary Evaluation Benefit from Translation Evaluation?](https://aclanthology.org/2022.eval4nlp-1.3/) *— 2022 · Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems*
34. [From Simultaneous to Streaming Machine Translation by Leveraging Streaming History](https://aclanthology.org/2022.acl-long.480/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
35. [FrugalScore: Learning Cheaper, Lighter and Faster Evaluation Metrics for Automatic Text Generation](https://aclanthology.org/2022.acl-long.93/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
36. [Fully-Semantic Parsing and Generation: the BabelNet Meaning Representation](https://aclanthology.org/2022.acl-long.121/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
37. [Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation](https://aclanthology.org/2022.naacl-main.51/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
38. [GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation](https://aclanthology.org/2022.coling-1.506/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
39. [GCPG: A General Framework for Controllable Paraphrase Generation](https://aclanthology.org/2022.findings-acl.318/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
40. [GEMv2: Multilingual NLG Benchmarking in a Single Line of Code](https://aclanthology.org/2022.emnlp-demos.27/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
41. [GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation](https://aclanthology.org/2022.emnlp-main.787/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
42. [GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://aclanthology.org/2022.acl-long.26/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
43. [GRS: Combining Generation and Revision in Unsupervised Sentence Simplification](https://aclanthology.org/2022.findings-acl.77/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
44. [GTCOM Neural Machine Translation Systems for WMT22](https://aclanthology.org/2022.wmt-1.39/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
45. [Gaussian Multi-head Attention for Simultaneous Machine Translation](https://aclanthology.org/2022.findings-acl.238/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
46. [Generating Coherent and Informative Descriptions for Groups of Visual Objects and Categories: A Simple Decoding Approach](https://aclanthology.org/2022.inlg-main.9/) *— 2022 · Proceedings of the 15th International Conference on Natural Language Generation*
47. [Generating Monolingual Dataset for Low Resource Language Bodo from old books using Google Keep](https://aclanthology.org/2022.lrec-1.705/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
48. [Generating Questions from Wikidata Triples](https://aclanthology.org/2022.lrec-1.29/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
49. [Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task](https://aclanthology.org/2022.lrec-1.379/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
50. [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*
51. [Generative Pretraining for Paraphrase Evaluation](https://aclanthology.org/2022.acl-long.280/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
52. [Genre Transfer in NMT:Creating Synthetic Spoken Parallel Sentences using Written Parallel Data](https://aclanthology.org/2022.icon-main.28/) *— 2022 · Proceedings of the 19th International Conference on Natural Language Processing (ICON)*
53. [Geographical Distance Is The New Hyperparameter: A Case Study Of Finding The Optimal Pre-trained Language For English-isiZulu Machine Translation.](https://aclanthology.org/2022.mia-1.1/) *— 2022 · Proceedings of the Workshop on Multilingual Information Access (MIA)*
54. [German Phoneme Recognition with Text-to-Phoneme Data Augmentation](https://arxiv.org/abs/2211.13776) *— 2022 · arXiv:2211.13776*
55. [Global Readiness of Language Technology for Healthcare: What Would It Take to Combat the Next Pandemic?](https://aclanthology.org/2022.coling-1.381/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
56. [GraDA: Graph Generative Data Augmentation for Commonsense Reasoning](https://aclanthology.org/2022.coling-1.397/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
57. [Gradient-guided Unsupervised Text Style Transfer via Contrastive Learning](https://arxiv.org/abs/2202.00469) *— 2022 · arXiv:2202.00469*
58. [Grafting Pre-trained Models for Multimodal Headline Generation](https://aclanthology.org/2022.emnlp-industry.25/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track*
59. [Graph Pre-training for AMR Parsing and Generation](https://aclanthology.org/2022.acl-long.415/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [Graph-based Keyword Planning for Legal Clause Generation from Topics](https://aclanthology.org/2022.nllp-1.26/) *— 2022 · Proceedings of the Natural Legal Language Processing Workshop 2022*
61. [Graph-to-Text Generation with Dynamic Structure Pruning](https://aclanthology.org/2022.coling-1.534/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
62. [Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation](https://aclanthology.org/2022.findings-emnlp.547/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
63. [Grounding in social media: An approach to building a chit-chat dialogue model](https://aclanthology.org/2022.naacl-srw.2/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop*
64. [Guiding Neural Machine Translation with Semantic Kernels](https://aclanthology.org/2022.findings-emnlp.541/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
65. [Guiding Neural Story Generation with Reader Models](https://aclanthology.org/2022.findings-emnlp.526/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
66. [Guiding Visual Question Generation](https://aclanthology.org/2022.naacl-main.118/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
67. [GuoFeng: A Benchmark for Zero Pronoun Recovery and Translation](https://aclanthology.org/2022.emnlp-main.774/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
68. [HAWP: a Dataset for Hindi Arithmetic Word Problem Solving](https://aclanthology.org/2022.lrec-1.373/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
69. [HECTOR: A Hybrid TExt SimplifiCation TOol for Raw Texts in French](https://aclanthology.org/2022.lrec-1.493/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
70. [HIBRIDS: Attention with Hierarchical Biases for Structure-aware Long Document Summarization](https://aclanthology.org/2022.acl-long.58/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
71. [HMIST: Hierarchical Multilingual Isometric Speech Translation using Multi-Task Learning Framework and it”s influence on Automatic Dubbing](https://aclanthology.org/2022.paclic-1.61/) *— 2022 · Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation*
72. [HaRiM$^+$: Evaluating Summary Quality with Hallucination Risk](https://aclanthology.org/2022.aacl-main.66/) *— 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 1: Long Papers)*
73. [Hard Gate Knowledge Distillation - Leverage Calibration for Robust and Reliable Language Model](https://aclanthology.org/2022.emnlp-main.665/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
74. [Harnessing Abstractive Summarization for Fact-Checked Claim Detection](https://aclanthology.org/2022.coling-1.259/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
75. [HeLo: Learning-Free Lookahead Decoding for Conversation Infilling](https://aclanthology.org/2022.findings-emnlp.367/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
76. [Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators](https://aclanthology.org/2022.emnlp-main.371/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
77. [HiTab: A Hierarchical Table Dataset for Question Answering and Natural Language Generation](https://aclanthology.org/2022.acl-long.78/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
78. [Hierarchical Recurrent Aggregative Generation for Few-Shot NLG](https://aclanthology.org/2022.findings-acl.170/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
79. [High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics](https://aclanthology.org/2022.tacl-1.47/) *— 2022 · Transactions of the Association for Computational Linguistics*
80. [History-Aware Hierarchical Transformer for Multi-session Open-domain Dialogue System](https://aclanthology.org/2022.findings-emnlp.247/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
81. [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)*
82. [How Far are We from Robust Long Abstractive Summarization?](https://aclanthology.org/2022.emnlp-main.172/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
83. [How Robust is Neural Machine Translation to Language Imbalance in Multilingual Tokenizer Training?](https://aclanthology.org/2022.amta-research.8/) *— 2022 · Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)*
84. [Human Evaluation and Correlation with Automatic Metrics in Consultation Note Generation](https://aclanthology.org/2022.acl-long.394/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
85. [Human Judgement as a Compass to Navigate Automatic Metrics for Formality Transfer](https://aclanthology.org/2022.humeval-1.9/) *— 2022 · Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)*
86. [Human Ratings Do Not Reflect Downstream Utility: A Study of Free-Text Explanations for Model Predictions](https://aclanthology.org/2022.blackboxnlp-1.14/) *— 2022 · Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
87. [Human evaluation of web-crawled parallel corpora for machine translation](https://aclanthology.org/2022.humeval-1.4/) *— 2022 · Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval)*
88. [Hypoformer: Hybrid Decomposition Transformer for Edge-friendly Neural Machine Translation](https://aclanthology.org/2022.emnlp-main.475/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
89. [IIT Bombay's WMT22 Automatic Post-Editing Shared Task Submission](https://aclanthology.org/2022.wmt-1.67/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
90. [IM2: an Interpretable and Multi-category Integrated Metric Framework for Automatic Dialogue Evaluation](https://aclanthology.org/2022.emnlp-main.762/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
91. [IMPARA: Impact-Based Metric for GEC Using Parallel Data](https://aclanthology.org/2022.coling-1.316/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
92. [IRAC: A Domain-Specific Annotated Corpus of Implicit Reasoning in Arguments](https://aclanthology.org/2022.lrec-1.499/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
93. [IRB-NLP at SemEval-2022 Task 1: Exploring the Relationship Between Words and Their Semantic Representations](https://aclanthology.org/2022.semeval-1.5/) *— 2022 · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)*
94. [Identifying Weaknesses in Machine Translation Metrics Through Minimum Bayes Risk Decoding: A Case Study for COMET](https://aclanthology.org/2022.aacl-main.83/) *— 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 1: Long Papers)*
95. [Image Caption Generation for Low-Resource Assamese Language](https://aclanthology.org/2022.rocling-1.33/) *— 2022 · Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)*
96. [Impact of Evaluation Methodologies on Code Summarization](https://aclanthology.org/2022.acl-long.339/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
97. [Improving Bot Response Contradiction Detection via Utterance Rewriting](https://aclanthology.org/2022.sigdial-1.56/) *— 2022 · Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue*
98. [Improving Chinese Story Generation via Awareness of Syntactic Dependencies and Semantics](https://aclanthology.org/2022.aacl-short.23/) *— 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)*
99. [Improving Compositional Generalization with Self-Training for Data-to-Text Generation](https://aclanthology.org/2022.acl-long.289/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
100. [Improving Conversational Recommendation Systems' Quality with Context-Aware Item Meta-Information](https://aclanthology.org/2022.findings-naacl.4/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*

Pages: [1](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/) · … · [47](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/47/) · **48** · [49](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/49/) · … · [109](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/cited-by/page/109/)