Machine Translation Evaluation with BERT Regressor
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Abstract (arXiv)
We introduce the metric using BERT (Bidirectional Encoder Representations from Transformers) (Devlin et al., 2019) for automatic machine translation evaluation. The experimental results of the WMT-2017 Metrics Shared Task dataset show that our metric achieves state-of-the-art performance in segment-level metrics task for all to-English language pairs.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Jul 2019.
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Citing papers per year: 2021: 3; 2022: 2; 2023: 0; 2024: 1.
6 papers.
- 2021Ditch the Gold Standard: Re-evaluating Conversational Question Answeringcited by 19
- 2021Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approachcited by 16
- 2021Naturalness Evaluation of Natural Language Generation in Task-oriented Dialogues using BERTcited by 5
- 2022BERTHA: Video Captioning Evaluation Via Transfer-Learned Human Assessmentcited by 3
- 2024Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Reviewcited by 3
- 2022SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encodercited by 0
- 2024Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review26 Sep 2024
- 2022SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encoder11 Jul 2022
- 2022BERTHA: Video Captioning Evaluation Via Transfer-Learned Human Assessment25 Jan 2022
- 2021Ditch the Gold Standard: Re-evaluating Conversational Question Answering16 Dec 2021
- 2021Naturalness Evaluation of Natural Language Generation in Task-oriented Dialogues using BERT7 Sep 2021
- 2021Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach20 Feb 2021