智能系统学报2024，Vol.19Issue(6)：1351-1365,15.DOI:10.11992/tis.202309036
大语言模型及其个性化推荐研究
Research on large language models and personalized recommendation
摘要
Abstract
Large language models have revolutionized natural language processing within artificial intelligence,signific-antly advancing personalized recommendation systems.This paper provides an in-depth analysis of existing research on large language models and their application in personalized recommendations.It explores the process of large language model recommendation and thoroughly analyzes the main research advancements from four perspectives:direct recom-mendation,representation learning-based recommendation,generation-based recommendation,and prompt learning re-commendation.The study identifies several challenges in current research on large language model recommendation,in-cluding recommendation bias,vulnerability to prompts,limited contextual understanding,high latency,fairness issues,and evaluation difficulties.It also presents future directions for research on large language model recommendation,in-cluding enhancing the security of large language model recommendations,developing domain-oriented large language model recommendations,exploring cross-modal large language model recommendations,integrating retrieval tasks with large language model recommendations,and improving the interpretability of large language model recommendations.关键词
大语言模型/推荐/深度学习/监督微调/对齐/提示学习/生成性/多模态Key words
large language model/recommendation/deep learning/supervised fine-tuning/alignment/prompt learning/generative/multimodal分类
信息技术与安全科学引用本文复制引用
吴国栋,秦辉,胡全兴,王雪妮,吴贞畅..大语言模型及其个性化推荐研究[J].智能系统学报,2024,19(6):1351-1365,15.基金项目
国家自然科学基金项目(32371993) （32371993）
安徽省自然科学基金项目(2108085MF209) （2108085MF209）
安徽省科技重大专项(202103b06020013). （202103b06020013）
