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Large Language Models (LLMs) are gaining momentum in software development with prompt-driven programming enabling developers to create code from natural language (NL) instructions.
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Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023 . OpenReview.net
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Large Language Models are Human-Level Prompt Engineers. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023 . OpenReview.net
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Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024 - Volume 1: Long Papers, St. Julian’s, Malta, March 17-22, 2024 , Yvette Graham and Matthew Purver (Eds.). Association for Computational Linguistics, 67–93
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Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, Bangkok, Thailand, August 11-16, 2024 , Lun-Wei Ku, Andre Martins, and Vivek Srikumar (Eds.). Association for Computational Linguistics, 14116–14137
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Quality Assessment of ChatGPT Generated Code and their Use by Developers. In 21st IEEE/ACM International Conference on Mining Software Repositories, MSR 2024, Lisbon, Portugal, April 15-16, 2024 , Diomidis Spinellis, Alberto Bacchelli, and Eleni Constantinou (Eds.). ACM, 152–156
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