---
title: "Who cites Results of WMT22 Metrics Shared Task: Stop Using…"
description: "The papers of the Elamur Research library that cite «Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust»…"
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# Who cites «Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust» · page 3

251 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/freitag-2022-results-wmt22-metrics-shared-task/)

Pages: [1](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/cited-by/) · [2](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/cited-by/page/2/) · **3**

1. [Exploring Context-Aware Evaluation Metrics for Machine Translation](https://aclanthology.org/2023.findings-emnlp.1021/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
2. [Exploring Prompting Large Language Models as Explainable Metrics](https://aclanthology.org/2023.eval4nlp-1.18/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
3. [GATITOS: Using a New Multilingual Lexicon for Low-resource Machine Translation](https://aclanthology.org/2023.emnlp-main.26/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
4. [GEMBA-MQM: Detecting Translation Quality Error Spans with GPT-4](https://aclanthology.org/2023.wmt-1.64/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
5. [HIT-MI&T Lab's Submission to Eval4NLP 2023 Shared Task](https://aclanthology.org/2023.eval4nlp-1.11/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
6. [ICE-Score: Instructing Large Language Models to Evaluate Code](https://arxiv.org/abs/2304.14317) *— 2023 · arXiv:2304.14317*
7. [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*
8. [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*
9. [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*
10. [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*
11. [KG-IQES: An Interpretable Quality Estimation System for Machine Translation Based on Knowledge Graph](https://aclanthology.org/2023.mtsummit-users.15/) *— 2023 · Proceedings of Machine Translation Summit XIX, Vol. 2: Users Track*
12. [L”évaluation de la traduction automatique du caractère au document : un état de l”art](https://aclanthology.org/2023.jeptalnrecital-rjc.10/) *— 2023 · Actes de CORIA-TALN 2023. Actes des 16e Rencontres Jeunes Chercheurs en RI (RJCRI) et 25e Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL)*
13. [LTRC_IIITH's 2023 Submission for Prompting Large Language Models as Explainable Metrics Task](https://aclanthology.org/2023.eval4nlp-1.13/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
14. [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*
15. [Little Giants: Exploring the Potential of Small LLMs as Evaluation Metrics in Summarization in the Eval4NLP 2023 Shared Task](https://aclanthology.org/2023.eval4nlp-1.17/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
16. [MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods](https://arxiv.org/abs/2309.10966) *— 2023 · arXiv:2309.10966*
17. [MEE4 and XLsim : IIIT HYD”s Submissions” for WMT23 Metrics Shared Task](https://aclanthology.org/2023.wmt-1.66/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
18. [MT Metrics Correlate with Human Ratings of Simultaneous Speech Translation](https://aclanthology.org/2023.iwslt-1.12/) *— 2023 · Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)*
19. [Metric Score Landscape Challenge (MSLC23): Understanding Metrics” Performance on a Wider Landscape of Translation Quality](https://aclanthology.org/2023.wmt-1.65/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
20. [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*
21. [Overview of the Second Shared Task on Automatic Minuting (AutoMin) at INLG 2023](https://aclanthology.org/2023.inlg-genchal.19/) *— 2023 · Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges*
22. [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*
23. [PaLM 2 Technical Report](https://arxiv.org/abs/2305.10403) *— 2023 · arXiv:2305.10403*
24. [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*
25. [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*
26. [Quality Estimation Using Minimum Bayes Risk](https://aclanthology.org/2023.wmt-1.67/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
27. [Reference-Free Summarization Evaluation with Large Language Models](https://aclanthology.org/2023.eval4nlp-1.16/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
28. [Reinforced Self-Training (ReST) for Language Modeling](https://arxiv.org/abs/2308.08998) *— 2023 · arXiv:2308.08998*
29. [Reranking for Natural Language Generation from Logical Forms: A Study based on Large Language Models](https://aclanthology.org/2023.ijcnlp-main.69/) *— 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
30. [Semantically-Informed Regressive Encoder Score](https://aclanthology.org/2023.wmt-1.69/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
31. [Separating the Wheat from the Chaff with BREAD: An open-source benchmark and metrics to detect redundancy in text](https://aclanthology.org/2023.gem-1.27/) *— 2023 · Proceedings of the Third Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
32. [Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models](https://arxiv.org/abs/2304.01852) *— 2023 · arXiv:2304.01852 · Meta-Radiology (2023)100017*
33. [TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks](https://arxiv.org/abs/2310.00752) *— 2023 · arXiv:2310.00752*
34. [Team NLLG submission for Eval4NLP 2023 Shared Task: Retrieval-Augmented In-Context Learning for NLG Evaluation](https://aclanthology.org/2023.eval4nlp-1.19/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
35. [The Devil Is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation](https://aclanthology.org/2023.wmt-1.100/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
36. [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*
37. [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)*
38. [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*
39. [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*
40. [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*
41. [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*
42. [Towards Effective Disambiguation for Machine Translation with Large Language Models](https://aclanthology.org/2023.wmt-1.44/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
43. [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*
44. [Towards Formality-Aware Neural Machine Translation by Leveraging Context Information](https://aclanthology.org/2023.findings-emnlp.494/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
45. [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*
46. [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*
47. [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*
48. [Which is better? Exploring Prompting Strategy For LLM-based Metrics](https://aclanthology.org/2023.eval4nlp-1.14/) *— 2023 · Proceedings of the 4th Workshop on Evaluation and Comparison of NLP Systems*
49. [eBLEU: Unexpectedly Good Machine Translation Evaluation Using Simple Word Embeddings](https://aclanthology.org/2023.wmt-1.61/) *— 2023 · Proceedings of the Eighth Conference on Machine Translation*
50. [COMET-22: Unbabel-IST 2022 Submission for the Metrics Shared Task](https://aclanthology.org/2022.wmt-1.52/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*
51. [Robust MT Evaluation with Sentence-level Multilingual Augmentation](https://aclanthology.org/2022.wmt-1.43/) *— 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)*

Pages: [1](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/cited-by/) · [2](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/cited-by/page/2/) · **3**