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
Date
2023
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
Place
Singapore
Publisher
Association for Computational Linguistics
Pages
13921-13937
Language
en
Short Title
CodeBERTScore
Accessed
26/03/2024, 19:33
Library Catalogue
DOI.org (Crossref)
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
Technical methods
Link to this record