id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-30144	Ma, Zhiyuan; Wu, Jie	Design of an LLM-Driven Personalized Learning Resource Recommendation System: -- A Comparative Study	2025	4	.pdf	application/pdf	2332	121	30	Developers need not consider local computational resources for training and deploying recommendation models, which reduces the usage threshold of recommendation platforms. Prompt Tuning In recommendation systems and LLM applications, Fine - Tuning and Prompt Tuning is essential to enhance the LLM's task performing ability.[2] Since the platform is implemented by connecting to existing LLMs through an API for recommendations, Prompt Tuning is used to fine-tune the LLM.	cache/fcis-30144.pdf	txt/fcis-30144.txt