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This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs).
Chat-rec: Towards interactive and explainable llms-augmented recommender system
Yunfan Gao, Tao Sheng, Youlin Xiang, Yun Xiong, Haofen Wang, and Jiawei Zhang. 2023 · 2023
Earlier work this paper cites.
Large language models are zero-shot rankers for recommender systems
Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian McAuley, and Wayne Xin Zhao. 2023 · 2023
Earlier work this paper cites.
Recommender ai agent: Integrating large language models for interactive recommendations
Xu Huang, Jianxun Lian, Yuxuan Lei, Jing Yao, Defu Lian, and Xing Xie. 2023 · 2023
Earlier work this paper cites.
RecExplainer: Aligning Large Language Models for Recommendation Model Interpretability
Yuxuan Lei, Jianxun Lian, Jing Yao, Xu Huang, Defu Lian, and Xing Xie. 2023 · 2023
Cited alongside, same era.
Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations
Jing Yao, Wei Xu, Jianxun Lian, Xiting Wang, Xiaoyuan Yi, and Xing Xie. 2023 · 2023
Cited alongside, same era.
Aligning Language Models for Versatile Text-based Item Retrieval
Yuxuan Lei, Jianxun Lian, Jing Yao, Mingqi Wu, Defu Lian, and Xing Xie. 2024 · 2024
Closest in time.
Aligning Large Language Models for Controllable Recommendations
Wensheng Lu, Jianxun Lian, Wei Zhang, Guanghua Li, Mingyang Zhou, Hao Liao, and Xing Xie. 2024 · 2024
Closest in time.
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