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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Principais autores:	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
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-04-01
Series:	Big Data and Cognitive Computing
Assuntos:	large language models (LLM) fine-tuning hermeneutics comprehension tutorial fine-tuning human–AI co-evolution
Acceso en liña:	https://www.mdpi.com/2504-2289/9/4/87
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LLM Fine-Tuning: Concepts, Opportunities, and Challenges

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