LLM Fine-Tuning: Concepts, Opportunities, and Challenges

As a foundation of large language models, fine-tuning drives rapid progress, broad applicability, and profound impacts on human–AI collaboration, surpassing earlier technological advancements. This paper provides a comprehensive overview of large language model (LLM) fine-tuning by integrating herme...

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Bibliographic Details

Published in:	Big Data and Cognitive Computing
Main Authors:	Xiao-Kun Wu, Min Chen, Wanyi Li, Rui Wang, Limeng Lu, Jia Liu, Kai Hwang, Yixue Hao, Yanru Pan, Qingguo Meng, Kaibin Huang, Long Hu, Mohsen Guizani, Naipeng Chao, Giancarlo Fortino, Fei Lin, Yonglin Tian, Dusit Niyato, Fei-Yue Wang
Format:	Article
Language:	English
Published:	MDPI AG 2025-04-01
Subjects:	large language models (LLM) fine-tuning hermeneutics comprehension tutorial fine-tuning human–AI co-evolution
Online Access:	https://www.mdpi.com/2504-2289/9/4/87