---
title: "Who cites METEOR: An Automatic Metric for MT Evaluation…"
description: "The papers of the Elamur Research library that cite «METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments», found…"
canonical: "https://research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/14/"
---
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# Who cites «METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments» · page 14

2025 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/banerjee-2005-meteor-automatic-metric-mt-evaluation/)

Pages: [1](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/) · … · [13](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/13/) · **14** · [15](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/15/) · … · [21](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/21/)

1. [Visual Spatial Description: Controlled Spatial-Oriented Image-to-Text Generation](https://aclanthology.org/2022.emnlp-main.93/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
2. [WDV: A Broad Data Verbalisation Dataset Built from Wikidata](https://arxiv.org/abs/2205.02627) *— 2022 · arXiv:2205.02627*
3. [Where to Go for the Holidays: Towards Mixed-Type Dialogs for Clarification of User Goals](https://aclanthology.org/2022.acl-long.73/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
4. [WikiOmnia: filtration and evaluation of the generated QA corpus on the whole Russian Wikipedia](https://aclanthology.org/2022.gem-1.10/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
5. [Your Answer is Incorrect... Would you like to know why? Introducing a Bilingual Short Answer Feedback Dataset](https://aclanthology.org/2022.acl-long.587/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
6. [uFACT: Unfaithful Alien-Corpora Training for Semantically Consistent Data-to-Text Generation](https://aclanthology.org/2022.findings-acl.223/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
7. [生成,推理与排序:基于多任务架构的数学文字题生成(Generating, Reasoning & Ranking: Multitask Learning Framework for Math Word Problem Generation)](https://aclanthology.org/2022.ccl-1.17/) *— 2022 · Proceedings of the 21st Chinese National Conference on Computational Linguistics*
8. [融合提示学习的故事生成方法(A Story Generation Method Incorporating Prompt Learning)](https://aclanthology.org/2022.ccl-1.16/) *— 2022 · Proceedings of the 21st Chinese National Conference on Computational Linguistics*
9. [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*
10. [A First Look: Towards Explainable TextVQA Models via Visual and Textual Explanations](https://aclanthology.org/2021.maiworkshop-1.4/) *— 2021 · Proceedings of the Third Workshop on Multimodal Artificial Intelligence*
11. [A Tutorial on Evaluation Metrics used in Natural Language Generation](https://aclanthology.org/2021.naacl-tutorials.4/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorials*
12. [A View From the Crowd: Evaluation Challenges for Time-Offset Interaction Applications](https://aclanthology.org/2021.humeval-1.9/) *— 2021 · Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)*
13. [ALL Dolphins Are Intelligent and SOME Are Friendly: Probing BERT for Nouns” Semantic Properties and their Prototypicality](https://aclanthology.org/2021.blackboxnlp-1.7/) *— 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
14. [Adaptive Fusion Techniques for Multimodal Data](https://aclanthology.org/2021.eacl-main.275/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
15. [Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling](https://aclanthology.org/2021.eacl-main.203/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
16. [An Efficient Keyframes Selection Based Framework for Video Captioning](https://aclanthology.org/2021.icon-main.29/) *— 2021 · Proceedings of the 18th International Conference on Natural Language Processing (ICON)*
17. [An analysis of document graph construction methods for AMR summarization](https://arxiv.org/abs/2111.13993) *— 2021 · arXiv:2111.13993*
18. [Ask what”s missing and what”s useful: Improving Clarification Question Generation using Global Knowledge](https://aclanthology.org/2021.naacl-main.340/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
19. [Assessing Dialogue Systems with Distribution Distances](https://aclanthology.org/2021.findings-acl.193/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
20. [Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots](https://aclanthology.org/2021.findings-emnlp.347/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
21. [Automatic Rephrasing of Transcripts-based Action Items](https://aclanthology.org/2021.findings-acl.253/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
22. [Automatic Text Evaluation through the Lens of Wasserstein Barycenters](https://aclanthology.org/2021.emnlp-main.817/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
23. [Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval](https://aclanthology.org/2021.emnlp-main.566/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
24. [Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation](https://aclanthology.org/2021.acl-long.562/) *— 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)*
25. [Biais de genre dans un système de traduction automatiqueneuronale : une étude préliminaire (Gender Bias in Neural Translation : a preliminary study )](https://aclanthology.org/2021.jeptalnrecital-taln.2/) *— 2021 · Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale*
26. [Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation](https://aclanthology.org/2021.acl-long.468/) *— 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)*
27. [Building the Directed Semantic Graph for Coherent Long Text Generation](https://aclanthology.org/2021.emnlp-main.200/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
28. [CIDEr-R: Robust Consensus-based Image Description Evaluation](https://aclanthology.org/2021.wnut-1.39/) *— 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)*
29. [CLIPScore: A Reference-free Evaluation Metric for Image Captioning](https://aclanthology.org/2021.emnlp-main.595/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
30. [ChainCQG: Flow-Aware Conversational Question Generation](https://aclanthology.org/2021.eacl-main.177/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
31. [Chinese Character Decomposition for Neural MT with Multi-Word Expressions](https://aclanthology.org/2021.nodalida-main.35/) *— 2021 · Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)*
32. [CoDesc: A Large Code–Description Parallel Dataset](https://aclanthology.org/2021.findings-acl.18/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
33. [CodeQA: A Question Answering Dataset for Source Code Comprehension](https://aclanthology.org/2021.findings-emnlp.223/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
34. [Commonsense-Focused Dialogues for Response Generation: An Empirical Study](https://aclanthology.org/2021.sigdial-1.13/) *— 2021 · Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue*
35. [Competence-based Multimodal Curriculum Learning for Medical Report Generation](https://aclanthology.org/2021.acl-long.234/) *— 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)*
36. [Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation](https://aclanthology.org/2021.emnlp-main.599/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
37. [ConQuest: Contextual Question Paraphrasing through Answer-Aware Synthetic Question Generation](https://aclanthology.org/2021.wnut-1.25/) *— 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)*
38. [Context Matters in Semantically Controlled Language Generation for Task-oriented Dialogue Systems](https://aclanthology.org/2021.icon-main.18/) *— 2021 · Proceedings of the 18th International Conference on Natural Language Processing (ICON)*
39. [Contrastive Attention for Automatic Chest X-ray Report Generation](https://aclanthology.org/2021.findings-acl.23/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
40. [Contrastive Multi-document Question Generation](https://aclanthology.org/2021.eacl-main.2/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
41. [Control Image Captioning Spatially and Temporally](https://aclanthology.org/2021.acl-long.157/) *— 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)*
42. [CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization](https://aclanthology.org/2021.emnlp-main.164/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
43. [Dealing with the Paradox of Quality Estimation](https://aclanthology.org/2021.mtsummit-loresmt.1/) *— 2021 · Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021)*
44. [Difficulty-Aware Machine Translation Evaluation](https://aclanthology.org/2021.acl-short.5/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
45. [Diversity and Consistency: Exploring Visual Question-Answer Pair Generation](https://aclanthology.org/2021.findings-emnlp.91/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
46. [Do Language Models Perform Generalizable Commonsense Inference?](https://aclanthology.org/2021.findings-acl.322/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
47. [ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning](https://aclanthology.org/2021.eacl-main.104/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
48. [Empathetic Dialog Generation with Fine-Grained Intents](https://aclanthology.org/2021.conll-1.10/) *— 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
49. [Enhancing the Open-Domain Dialogue Evaluation in Latent Space](https://aclanthology.org/2021.findings-acl.432/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
50. [Entity-Based Semantic Adequacy for Data-to-Text Generation](https://aclanthology.org/2021.findings-emnlp.132/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
51. [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)*
52. [Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/) *— our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
53. [Evaluation Guidelines to Deal with Implicit Phenomena to Assess Factuality in Data-to-Text Generation](https://aclanthology.org/2021.unimplicit-1.3/) *— 2021 · Proceedings of the 1st Workshop on Understanding Implicit and Underspecified Language*
54. [Evaluation of Review Summaries via Question-Answering](https://aclanthology.org/2021.alta-1.9/) *— 2021 · Proceedings of the 19th Annual Workshop of the Australasian Language Technology Association*
55. [EventNarrative: A large-scale Event-centric Dataset for Knowledge Graph-to-Text Generation](https://arxiv.org/abs/2111.00276) *— 2021 · arXiv:2111.00276*
56. [Explanations for CommonsenseQA: New Dataset and Models](https://aclanthology.org/2021.acl-long.238/) *— 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)*
57. [Exploring Metaphoric Paraphrase Generation](https://aclanthology.org/2021.conll-1.26/) *— 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
58. [Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models](https://aclanthology.org/2021.emnlp-main.445/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
59. [Exploring Structural Encoding for Data-to-Text Generation](https://aclanthology.org/2021.inlg-1.44/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
60. [Finding a Balanced Degree of Automation for Summary Evaluation](https://aclanthology.org/2021.emnlp-main.531/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
61. [Findings of the Second Workshop on Automatic Simultaneous Translation](https://aclanthology.org/2021.autosimtrans-1.6/) *— 2021 · Proceedings of the Second Workshop on Automatic Simultaneous Translation*
62. [Fine Grained Human Evaluation for English-to-Chinese Machine Translation: A Case Study on Scientific Text](https://arxiv.org/abs/2110.14766) *— 2021 · arXiv:2110.14766*
63. [Fingerprinting Fine-tuned Language Models in the Wild](https://aclanthology.org/2021.findings-acl.409/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
64. [GANDALF: a General Character Name Description Dataset for Long Fiction](https://aclanthology.org/2021.mrqa-1.13/) *— 2021 · Proceedings of the 3rd Workshop on Machine Reading for Question Answering*
65. [GEM: A General Evaluation Benchmark for Multimodal Tasks](https://aclanthology.org/2021.findings-acl.229/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
66. [GLGE: A New General Language Generation Evaluation Benchmark](https://aclanthology.org/2021.findings-acl.36/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
67. [GSum: A General Framework for Guided Neural Abstractive Summarization](https://aclanthology.org/2021.naacl-main.384/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
68. [Generalising Multilingual Concept-to-Text NLG with Language Agnostic Delexicalisation](https://aclanthology.org/2021.acl-long.10/) *— 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)*
69. [Generating Negative Samples by Manipulating Golden Responses for Unsupervised Learning of a Response Evaluation Model](https://aclanthology.org/2021.naacl-main.120/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
70. [Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine Translation](https://aclanthology.org/2021.acl-long.480/) *— 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)*
71. [GupShup: Summarizing Open-Domain Code-Switched Conversations](https://aclanthology.org/2021.emnlp-main.499/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
72. [HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations](https://aclanthology.org/2021.acl-long.283/) *— 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)*
73. [Hierarchical Context-aware Network for Dense Video Event Captioning](https://aclanthology.org/2021.acl-long.156/) *— 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)*
74. [HyKnow: End-to-End Task-Oriented Dialog Modeling with Hybrid Knowledge Management](https://aclanthology.org/2021.findings-acl.139/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
75. [IgSEG: Image-guided Story Ending Generation](https://aclanthology.org/2021.findings-acl.274/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
76. [Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentation](https://aclanthology.org/2021.findings-acl.357/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
77. [Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting](https://aclanthology.org/2021.emnlp-main.45/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
78. [Improving Text Auto-Completion with Next Phrase Prediction](https://aclanthology.org/2021.findings-emnlp.378/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
79. [Improving Unsupervised Question Answering via Summarization-Informed Question Generation](https://aclanthology.org/2021.emnlp-main.340/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
80. [Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs](https://aclanthology.org/2021.mrl-1.15/) *— 2021 · Proceedings of the 1st Workshop on Multilingual Representation Learning*
81. [JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs](https://aclanthology.org/2021.findings-acl.223/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
82. [KPQA: A Metric for Generative Question Answering Using Keyphrase Weights](https://aclanthology.org/2021.naacl-main.170/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
83. [Language-agnostic Representation from Multilingual Sentence Encoders for Cross-lingual Similarity Estimation](https://aclanthology.org/2021.emnlp-main.612/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
84. [Latent Reasoning for Low-Resource Question Generation](https://aclanthology.org/2021.findings-acl.265/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
85. [Learning Sequential and Structural Information for Source Code Summarization](https://aclanthology.org/2021.findings-acl.251/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
86. [Learning ULMFiT and Self-Distillation with Calibration for Medical Dialogue System](https://aclanthology.org/2021.icnlsp-1.22/) *— 2021 · Proceedings of the 4th International Conference on Natural Language and Speech Processing (ICNLSP 2021)*
87. [Learning to Generate Questions by Learning to Recover Answer-containing Sentences](https://aclanthology.org/2021.findings-acl.132/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
88. [MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers](https://arxiv.org/abs/2102.01454) *— 2021 · arXiv:2102.01454*
89. [MT-Telescope: An interactive platform for contrastive evaluation of MT systems](https://aclanthology.org/2021.acl-demo.9/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations*
90. [Macro-Average: Rare Types Are Important Too](https://aclanthology.org/2021.naacl-main.90/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
91. [Make the Blind Translator See The World: A Novel Transfer Learning Solution for Multimodal Machine Translation](https://aclanthology.org/2021.mtsummit-research.12/) *— 2021 · Proceedings of Machine Translation Summit XVIII: Research Track*
92. [Mention Flags (MF): Constraining Transformer-based Text Generators](https://aclanthology.org/2021.acl-long.9/) *— 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)*
93. [Mistake Captioning: A Machine Learning Approach for Detecting Mistakes and Generating Instructive Feedback](https://aclanthology.org/2021.ranlp-1.163/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
94. [Modeling Graph Structure via Relative Position for Text Generation from Knowledge Graphs](https://aclanthology.org/2021.textgraphs-1.2/) *— 2021 · Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15)*
95. [NUIG-DSI's submission to The GEM Benchmark 2021](https://aclanthology.org/2021.gem-1.13/) *— 2021 · Proceedings of the First Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
96. [Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study](https://aclanthology.org/2021.tacl-1.61/) *— 2021 · Transactions of the Association for Computational Linguistics*
97. [Naturalness Evaluation of Natural Language Generation in Task-oriented Dialogues Using BERT](https://aclanthology.org/2021.ranlp-1.96/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
98. [Novel Natural Language Summarization of Program Code via Leveraging Multiple Input Representations](https://aclanthology.org/2021.findings-emnlp.214/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
99. [O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning](https://aclanthology.org/2021.findings-acl.24/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
100. [OTTers: One-turn Topic Transitions for Open-Domain Dialogue](https://aclanthology.org/2021.acl-long.194/) *— 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)*

Pages: [1](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/) · … · [13](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/13/) · **14** · [15](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/15/) · … · [21](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/cited-by/page/21/)