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Enhancing Trust in LLM-Generated Code Summaries with Calibrated Confidence Scores
May 1, 2024, 4:48 a.m. | Yuvraj Virk, Premkumar Devanbu, Toufique Ahmed
cs.CL updates on arXiv.org arxiv.org
Abstract: A good summary can often be very useful during program comprehension. While a brief, fluent, and relevant summary can be helpful, it does require significant human effort to produce. Often, good summaries are unavailable in software projects, thus making maintenance more difficult. There has been a considerable body of research into automated AI-based methods, using Large Language models (LLMs), to generate summaries of code; there also has been quite a bit work on ways to …
abstract arxiv code confidence cs.cl cs.se generated good human llm maintenance making projects software summary trust type while
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