[17] Sonia Haiduc, Jairo Aponte, Laura Moreno, and Andrian Marcus. 2010. On the use of automated text summarization techniques for summarizing source code. In 2010 17th Working Conference on Reverse Engineering. IEEE, 35-44.
[18] Xing Hu, Ge Li, Xin Xia, David Lo, and Zhi Jin. 2018. Deep code comment generation. In 2018 IEEE/ACM 26th International Conference on Program Comprehension (ICPC). IEEE, 200-20010.
[19] Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, Miltiadis Allamanis, and Marc Brockschmidt. 2019. Codesearchnet challenge: Evaluating the state of semantic code search. arXiv preprint arXiv:1909.09436 (2019).
[20] Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, and Luke Zettlemoyer. 2016. Summarizing source code using a neural attention model. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2073-2083.
[21] Alexander LeClair, Siyuan Jiang, and Collin McMillan. 2019. A neural model for generating natural language summaries of program subroutines. In 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE). IEEE, 795-806.
[22] Jia Li, Yongmin Li, Ge Li, Xing Hu, Xin Xia, and Zhi Jin. 2021. Editsum: A retrieve-and-edit framework for source code summarization. In 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, 155-166.
[23] Chin-Yew Lin. 2004. ROUGE: A Package for Automatic Evaluation of Summaries. In Text Summarization Branches Out. Association for Computational Linguistics, Barcelona, Spain, 74-81. https://aclanthology.org/W04-1013
[24] Chin-Yew Lin and Franz Josef Och. 2004. ORANGE: a Method for Evaluating Automatic Evaluation Metrics for Machine Translation. In COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics. COLING, Geneva, Switzerland, 501-507. https://aclanthology.org/C04-1072
[25] Shangqing Liu, Yu Chen, Xiaofei Xie, Jingkai Siow, and Yang Liu. 2020. Retrieval-augmented generation for code summarization via hybrid gnn. arXiv preprint arXiv:2006.05405 (2020).
[26] Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. arXiv:1907.11692 [cs.CL]
[27] Paul W McBurney and Collin McMillan. 2014. Automatic documentation generation via source code summarization of method context. In Proceedings of the 22nd International Conference on Program Comprehension. 279–290.
[28] OpenAI. 2020. OpenAI GPT-3 Model. https://openai.com/gpt-3/
[29] Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022. Training language models to follow instructions with human feedback. arXiv preprint arXiv:2203.02155 (2022).
[30] Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311-318.
[31] Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J Liu, et al. 2020. Exploring the limits of transfer learning with a unified text-to-text transformer. J. Mach. Learn. Res. 21, 140 (2020), 1-67.
[32] Jianlin Su, Jiarun Cao, Weijie Liu, and Yangyiwen Ou. 2021. Whitening sentence representations for better semantics and faster retrieval. arXiv preprint arXiv:2103.15316 (2021).