BLEURT: Learning Robust Metrics for Text Generation
Article Status
Published
Authors/contributors
- Sellam, Thibault (Author)
- Das, Dipanjan (Author)
- Parikh, Ankur (Author)
Title
BLEURT: Learning Robust Metrics for Text Generation
Proceedings Title
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Conference Name
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Publisher
Association for Computational Linguistics
Place
Online
Date
2020
Pages
7881-7892
Citation Key
sellam2020
Accessed
16/10/2023, 19:38
Short Title
BLEURT
Language
en
Library Catalogue
DOI.org (Crossref)
Extra
<AI Smry>: BLEURT, a learned evaluation metric for English based on BERT, can model human judgment with a few thousand possibly biased training examples and yields superior results even when the training data is scarce and out-of-distribution.
<标题>: BLEURT：面向文本生成的鲁棒度量学习
Read_Status: New
Read_Status_Date: 2026-01-26T11:33:38.513Z
Citation
Sellam, T., Das, D., & Parikh, A. (2020). BLEURT: Learning Robust Metrics for Text Generation. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 7881–7892. https://doi.org/10.18653/v1/2020.acl-main.704
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