[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-7/)

[home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [cited-by](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/) / Who cites «COMET: A Neural Framework for MT Evaluation» · page 7

# Who cites «COMET: A Neural Framework for MT Evaluation» · page 7

1167 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/rei-2020-comet-neural-framework-mt-evaluation/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-6/) · **7** · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-9/) · [10](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-10/) · [11](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-11/) · [12](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-12/)

1. [Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus](https://aclanthology.org/2023.emnlp-main.873/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
2. [How effective is machine translation on low-resource code-switching? A case study comparing human and automatic metrics](https://aclanthology.org/2023.findings-acl.893/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
3. [Human-in-the-loop Machine Translation with Large Language Model](https://aclanthology.org/2023.mtsummit-users.8/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track*
4. [INSTRUCTSCORE: Towards Explainable Text Generation Evaluation with Automatic Feedback](https://aclanthology.org/2023.emnlp-main.365/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
5. [Improved Pseudo Data for Machine Translation Quality Estimation with Constrained Beam Search](https://aclanthology.org/2023.emnlp-main.764/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
6. [Improving Formality-Sensitive Machine Translation Using Data-Centric Approaches and Prompt Engineering](https://aclanthology.org/2023.iwslt-1.40/) *— 2023 · Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)*
7. [Improving Language Model Integration for Neural Machine Translation](https://aclanthology.org/2023.findings-acl.444/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
8. [Improving Translation Quality Estimation with Bias Mitigation](https://aclanthology.org/2023.acl-long.121/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
9. [In-Image Neural Machine Translation with Segmented Pixel Sequence-to-Sequence Model](https://aclanthology.org/2023.findings-emnlp.1004/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
10. [In-context Examples Selection for Machine Translation](https://aclanthology.org/2023.findings-acl.564/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
11. [IndicMT Eval: A Dataset to Meta-Evaluate Machine Translation Metrics for Indian Languages](https://aclanthology.org/2023.acl-long.795/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
12. [IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages](https://arxiv.org/abs/2305.16307) *— 2023 · arXiv:2305.16307*
13. [Integrating Translation Memories into Non-Autoregressive Machine Translation](https://aclanthology.org/2023.eacl-main.96/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
14. [Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM](https://arxiv.org/abs/2303.01911) *— 2023 · arXiv:2303.01911*
15. [Is ChatGPT a Good NLG Evaluator? A Preliminary Study](https://arxiv.org/abs/2303.04048) *— 2023 · arXiv:2303.04048*
16. [It''s MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk](https://aclanthology.org/2023.bigpicture-1.9/) *— 2023 · Proceedings of the Big Picture Workshop*
17. [JHU IWSLT 2023 Dialect Speech Translation System Description](https://aclanthology.org/2023.iwslt-1.26/) *— 2023 · Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)*
18. [JWSign: A Highly Multilingual Corpus of Bible Translations for more Diversity in Sign Language Processing](https://aclanthology.org/2023.findings-emnlp.664/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
19. [LENS: A Learnable Evaluation Metric for Text Simplification](https://aclanthology.org/2023.acl-long.905/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
20. [Large Language Models Are State-of-the-Art Evaluators of Translation Quality](https://aclanthology.org/2023.eamt-1.19/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
21. [Learning Answer Generation using Supervision from Automatic Question Answering Evaluators](https://aclanthology.org/2023.acl-long.467/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
22. [Learning Language-Specific Layers for Multilingual Machine Translation](https://aclanthology.org/2023.acl-long.825/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
23. [Learning Translation Quality Evaluation on Low Resource Languages from Large Language Models](https://arxiv.org/abs/2302.03491) *— 2023 · arXiv:2302.03491*
24. [Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing](https://aclanthology.org/2023.acl-long.177/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
25. [Leveraging GPT-4 for Automatic Translation Post-Editing](https://aclanthology.org/2023.findings-emnlp.804/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
26. [Leveraging Multilingual Knowledge Graph to Boost Domain-specific Entity Translation of ChatGPT](https://aclanthology.org/2023.mtsummit-users.7/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track*
27. [Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation](https://aclanthology.org/2023.eacl-main.75/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
28. [MMT's Submission for the WMT 2023 Quality Estimation Shared Task](https://aclanthology.org/2023.wmt-1.75/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
29. [MTCue: Learning Zero-Shot Control of Extra-Textual Attributes by Leveraging Unstructured Context in Neural Machine Translation](https://aclanthology.org/2023.findings-acl.521/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
30. [Machine Translation with Large Language Models: Prompting, Few-shot Learning, and Fine-tuning with QLoRA](https://aclanthology.org/2023.wmt-1.43/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
31. [Machine vs. Human: Exploring Syntax and Lexicon in German Translations, with a Spotlight on Anglicisms](https://aclanthology.org/2023.nodalida-1.22/) *— 2023 · Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)*
32. [MetricX-23: The Google Submission to the WMT 2023 Metrics Shared Task](https://aclanthology.org/2023.wmt-1.63/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
33. [Multi-Parallel Corpus of North Levantine Arabic](https://aclanthology.org/2023.arabicnlp-1.34/) *— 2023 · Proceedings of ArabicNLP 2023*
34. [Multidimensional Evaluation for Text Style Transfer Using ChatGPT](https://arxiv.org/abs/2304.13462) *— 2023 · arXiv:2304.13462*
35. [Multifaceted Challenge Set for Evaluating Machine Translation Performance](https://aclanthology.org/2023.wmt-1.22/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
36. [Multilingual Clinical NER: Translation or Cross-lingual Transfer?](https://aclanthology.org/2023.clinicalnlp-1.34/) *— 2023 · Proceedings of the 5th Clinical Natural Language Processing Workshop*
37. [NAIST-NICT WMT'23 General MT Task Submission](https://aclanthology.org/2023.wmt-1.7/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
38. [NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation](https://aclanthology.org/2023.emnlp-demo.26/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
39. [On the Blind Spots of Model-Based Evaluation Metrics for Text Generation](https://aclanthology.org/2023.acl-long.674/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
40. [Overview of Robust and Multilingual Automatic Evaluation Metrics for Open-Domain Dialogue Systems at DSTC 11 Track 4](https://arxiv.org/abs/2306.12794) *— 2023 · arXiv:2306.12794*
41. [PE effort and neural-based automatic MT metrics: do they correlate?](https://aclanthology.org/2023.eamt-1.31/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
42. [ParroT: Translating during Chat using Large Language Models tuned with Human Translation and Feedback](https://aclanthology.org/2023.findings-emnlp.1001/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
43. [Physician Detection of Clinical Harm in Machine Translation: Quality Estimation Aids in Reliance and Backtranslation Identifies Critical Errors](https://aclanthology.org/2023.emnlp-main.712/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
44. [Poor Man''s Quality Estimation: Predicting Reference-Based MT Metrics Without the Reference](https://aclanthology.org/2023.eacl-main.95/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
45. [Pre-Trained Language-Meaning Models for Multilingual Parsing and Generation](https://aclanthology.org/2023.findings-acl.345/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
46. [Prompting Large Language Model for Machine Translation: A Case Study](https://arxiv.org/abs/2301.07069) *— 2023 · arXiv:2301.07069*
47. [Pulling Out All The Full Stops: Punctuation Sensitivity in Neural Machine Translation and Evaluation](https://aclanthology.org/2023.findings-acl.381/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
48. [Quality Analysis of Multilingual Neural Machine Translation Systems and Reference Test Translations for the English-Romanian language pair in the Medical Domain](https://aclanthology.org/2023.eamt-1.35/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
49. [RAMP: Retrieval and Attribute-Marking Enhanced Prompting for Attribute-Controlled Translation](https://aclanthology.org/2023.acl-short.126/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
50. [RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question](https://aclanthology.org/2023.findings-acl.428/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
51. [Reference Free Domain Adaptation for Translation of Noisy Questions with Question Specific Rewards](https://aclanthology.org/2023.findings-emnlp.16/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
52. [Reinforced Self-Training (ReST) for Language Modeling](https://arxiv.org/abs/2308.08998) *— 2023 · arXiv:2308.08998*
53. [Responsibility Perspective Transfer for Italian Femicide News](https://aclanthology.org/2023.findings-acl.501/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
54. [Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent](https://aclanthology.org/2023.wmt-1.51/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
55. [Rethinking Round-Trip Translation for Machine Translation Evaluation](https://aclanthology.org/2023.findings-acl.22/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
56. [Return to the Source: Assessing Machine Translation Suitability](https://aclanthology.org/2023.eamt-1.9/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
57. [RoCS-MT: Robustness Challenge Set for Machine Translation](https://aclanthology.org/2023.wmt-1.21/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
58. [Robustness Tests for Automatic Machine Translation Metrics with Adversarial Attacks](https://aclanthology.org/2023.findings-emnlp.340/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
59. [SEAHORSE: A Multilingual, Multifaceted Dataset for Summarization Evaluation](https://aclanthology.org/2023.emnlp-main.584/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
60. [SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes](https://aclanthology.org/2023.acl-long.283/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
61. [SOTASTREAM: A Streaming Approach to Machine Translation Training](https://aclanthology.org/2023.nlposs-1.13/) *— 2023 · Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)*
62. [Semantically-Informed Regressive Encoder Score](https://aclanthology.org/2023.wmt-1.69/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
63. [Semi-supervised Learning for Quality Estimation of Machine Translation](https://aclanthology.org/2023.mtsummit-research.7/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 1: Research Track*
64. [Speaking Multiple Languages Affects the Moral Bias of Language Models](https://aclanthology.org/2023.findings-acl.134/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
65. [Speculative Decoding: Exploiting Speculative Execution for Accelerating Seq2seq Generation](https://aclanthology.org/2023.findings-emnlp.257/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
66. [Speech Translation with Style: AppTek''s Submissions to the IWSLT Subtitling and Formality Tracks in 2023](https://aclanthology.org/2023.iwslt-1.22/) *— 2023 · Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)*
67. [Steering Large Language Models for Machine Translation with Finetuning and In-Context Learning](https://aclanthology.org/2023.findings-emnlp.744/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
68. [Subset Retrieval Nearest Neighbor Machine Translation](https://aclanthology.org/2023.acl-long.10/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
69. [T5Score: Discriminative Fine-tuning of Generative Evaluation Metrics](https://aclanthology.org/2023.findings-emnlp.1014/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
70. [TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties](https://aclanthology.org/2023.arabicnlp-1.6/) *— 2023 · Proceedings of ArabicNLP 2023*
71. [TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks](https://arxiv.org/abs/2310.00752) *— 2023 · arXiv:2310.00752*
72. [Tackling Ambiguity with Images: Improved Multimodal Machine Translation and Contrastive Evaluation](https://aclanthology.org/2023.acl-long.295/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
73. [Tailoring Domain Adaptation for Machine Translation Quality Estimation](https://aclanthology.org/2023.eamt-1.2/) *— 2023 · Proceedings of the 24th Annual Conference of the European Association for Machine Translation*
74. [TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation](https://aclanthology.org/2023.acl-short.164/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
75. [Terminology-Aware Translation with Constrained Decoding and Large Language Model Prompting](https://aclanthology.org/2023.wmt-1.80/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
76. [Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization](https://aclanthology.org/2023.acl-long.47/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
77. [Text Style Transfer Back-Translation](https://aclanthology.org/2023.acl-long.441/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
78. [The Eval4NLP 2023 Shared Task on Prompting Large Language Models as Explainable Metrics](https://aclanthology.org/2023.eval4nlp-1.10/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
79. [The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics](https://aclanthology.org/2023.acl-short.94/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
80. [The OPUS-MT Dashboard – A Toolkit for a Systematic Evaluation of Open Machine Translation Models](https://aclanthology.org/2023.acl-demo.30/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)*
81. [The Role of Compounds in Human vs. Machine Translation Quality](https://aclanthology.org/2023.mtsummit-research.21/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 1: Research Track*
82. [There''s No Data like Better Data: Using QE Metrics for MT Data Filtering](https://aclanthology.org/2023.wmt-1.50/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
83. [Ties Matter: Meta-Evaluating Modern Metrics with Pairwise Accuracy and Tie Calibration](https://aclanthology.org/2023.emnlp-main.798/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
84. [Token-Level Self-Evolution Training for Sequence-to-Sequence Learning](https://aclanthology.org/2023.acl-short.73/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
85. [Tokengram_F, a Fast and Accurate Token-based chrF++ Derivative](https://aclanthology.org/2023.wmt-1.59/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
86. [Tokenization and the Noiseless Channel](https://aclanthology.org/2023.acl-long.284/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
87. [Toward Human-Like Evaluation for Natural Language Generation with Error Analysis](https://aclanthology.org/2023.acl-long.324/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
88. [Towards Better Evaluation for Formality-Controlled English-Japanese Machine Translation](https://aclanthology.org/2023.wmt-1.49/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
89. [Towards Example-Based NMT with Multi-Levenshtein Transformers](https://aclanthology.org/2023.emnlp-main.113/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
90. [Towards Explainable Evaluation Metrics for Machine Translation](https://arxiv.org/abs/2306.13041) *— 2023 · arXiv:2306.13041 · Journal of Machine Learning Research (JMLR), 2024, vol. 25, no. 75, p. 1-49*
91. [Towards Fine-Grained Information: Identifying the Type and Location of Translation Errors](https://arxiv.org/abs/2302.08975) *— 2023 · arXiv:2302.08975*
92. [Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation](https://aclanthology.org/2023.emnlp-main.1018/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
93. [Towards Large Language Model driven Reference-less Translation Evaluation for English and Indian Language](https://aclanthology.org/2023.icon-1.28/) *— 2023 · Proceedings of the 20th International Conference on Natural Language Processing (ICON)*
94. [Towards Making the Most of ChatGPT for Machine Translation](https://aclanthology.org/2023.findings-emnlp.373/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
95. [Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation](https://aclanthology.org/2023.acl-long.448/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
96. [Towards a Better Understanding of Variations in Zero-Shot Neural Machine Translation Performance](https://aclanthology.org/2023.emnlp-main.836/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
97. [Toxicity in Multilingual Machine Translation at Scale](https://aclanthology.org/2023.findings-emnlp.642/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
98. [Training and Meta-Evaluating Machine Translation Evaluation Metrics at the Paragraph Level](https://aclanthology.org/2023.wmt-1.96/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
99. [Transformers Go for the LOLs: Generating (Humourous) Titles from Scientific Abstracts End-to-End](https://aclanthology.org/2023.eval4nlp-1.6/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
100. [Treating General MT Shared Task as a Multi-Domain Adaptation Problem: HW-TSC''s Submission to the WMT23 General MT Shared Task](https://aclanthology.org/2023.wmt-1.16/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-3/) · [4](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-4/) · [5](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-5/) · [6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-6/) · **7** · [8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-8/) · [9](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-9/) · [10](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-10/) · [11](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-11/) · [12](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-12/)

- [← previous Who cites «COMET: A Neural Framework for MT Evaluation» · page 6](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-6/)
- [next → Who cites «COMET: A Neural Framework for MT Evaluation» · page 8](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/rei-2020-comet-neural-framework-mt-evaluation-8/)
- [↑ back to papers/cited-by/](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/)