Personalized Experiment Report Comments Auto-Generation and Application Based on Large Language Models

While reviewing computer experiment reports, assessment systems exhibit diversity and discrepancies. The rigid templates used for evaluation lack personalized content, and the results often fail to provide a basis for interpretability. To address these issues, this study proposes a personalized expe...

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Bibliographic Details

Published in:	Jisuanji gongcheng
Main Author:	Jie ZHAI, Yanhao LI, Binbin LI, Weibin GUO
Format:	Article
Language:	English
Published:	Editorial Office of Computer Engineering 2024-07-01
Subjects:	large language models|decision trees of experimental evaluation|personalization|comments auto-generation|code quality assessment
Online Access:	https://www.ecice06.com/fileup/1000-3428/PDF/20240705.pdf