Fine-Tuning Large Language Models for Answering Programming Questions with Code Snippets
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-36021-3_15
Reference28 articles.
1. Beau, N., Crabbé, B.: The impact of lexical and grammatical processing on generating code from natural language. In: Findings of the Association for Computational Linguistics: ACL 2022, pp. 2204–2214. Association for Computational Linguistics, Dublin, Ireland (2022). https://doi.org/10.18653/v1/2022.findings-acl.173
2. Beyer, S., Macho, C., Di Penta, M., Pinzger, M.: What kind of questions do developers ask on Stack Overflow? A comparison of automated approaches to classify posts into question categories. Empir. Softw. Eng. 25(3), 2258–2301 (2019). https://doi.org/10.1007/s10664-019-09758-x
3. Black, S., Gao, L., Wang, P., Leahy, C., Biderman, S.: GPT-Neo: large Scale autoregressive language modeling with mesh-tensorflow (2021). https://doi.org/10.5281/zenodo.5297715
4. Brown, T.B. et al.: Language models are few-shot learners (2020). https://doi.org/10.48550/ARXIV.2005.14165
5. Chen, M. et al.: Evaluating large language models trained on code. CoRR abs/2107.03374 (2021), https://arxiv.org/abs/2107.03374
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