CCAF: Learning Code Change via AdapterFusion
Author:
Affiliation:
1. Nanjing University, China
2. Software Institute, Nanjing University, China
Funder
National Key Research and Development Program of China
Natural Science Foundation of Jiangsu Province
Huawei Technologies
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3671016.3671399
Reference54 articles.
1. Shamil Ayupov and Nadezhda Chirkova. 2022. Parameter-Efficient Finetuning of Transformers for Source Code. arXiv preprint arXiv:2212.05901 (2022).
2. Satanjeev Banerjee and Alon Lavie. 2005. METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization. 65–72.
3. FIRA
4. Boa: A language and infrastructure for analyzing ultra-large-scale software repositories
5. CodeBERT: A Pre-Trained Model for Programming and Natural Languages
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