CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code
Article Status
Published
Authors/contributors
- Zhou, Shuyan (Author)
- Alon, Uri (Author)
- Agarwal, Sumit (Author)
- Neubig, Graham (Author)
Title
CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code
Proceedings Title
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Conference Name
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Publisher
Association for Computational Linguistics
Place
Singapore
Date
2023
Pages
13921-13937
Citation Key
zhou2023
Accessed
26/03/2024, 19:33
Short Title
CodeBERTScore
Language
en
Library Catalogue
DOI.org (Crossref)
Extra
<标题>: CodeBERTScore：使用预训练代码模型评估代码生成
Read_Status: New
Read_Status_Date: 2026-01-26T11:33:38.511Z
Citation
Zhou, S., Alon, U., Agarwal, S., & Neubig, G. (2023). CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 13921–13937. https://doi.org/10.18653/v1/2023.emnlp-main.859
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