Which Syntactic Capabilities Are Statistically Learned by Masked Language Models for Code?
Author:
Affiliation:
1. William & Mary, Williamsburg, Virginia, USA
2. William & Mary, Williamsburg, Virginia, United States of America
Funder
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3639476.3639768
Reference42 articles.
1. 2023. WM-SEMERU/SyntaxEval. https://github.com/WM-SEMERU/SyntaxEval original-date: 2022-09-09T20:53:59Z.
2. Toufique Ahmed Dian Yu Chengxuan Huang Cathy Wang et al. 2023. Towards Understanding What Code Language Models Learned. arXiv:2306.11943 [cs]. 10.48550/arXiv.2306.11943
3. Vaishak Belle and Ioannis Papantonis. 2020. Principles and Practice of Explainable Machine Learning. CoRR abs/2009.11698 (2020). arXiv:2009.11698 https://arxiv.org/abs/2009.11698
4. Learning from examples to improve code completion systems
5. SEQUENCER: Sequence-to-Sequence Learning for End-to-End Program Repair
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