Generative vs. Agentic Recommendation:Two LLM Paradigms for Recommender Systems, and the MemRec Framework
Shenzhen University, Shenzhen · Invited by Prof. Weike Pan
Email: chenweixin@kuaishou.com (work), me@weixinchen.com (general purpose)
Weixin Chen is an Applied Scientist at Kuaishou Technology, working on LLM-based recommendation through the Kuaishou K-Star Talent Program (快Star-X).
He received his Ph.D. from Hong Kong Baptist University, advised by Prof. Li Chen. He was a Visiting Scholar at Rutgers University, working with Prof. Yongfeng Zhang. He received his B.Eng. from Shenzhen University, advised by Prof. Weike Pan.
His research focuses on LLM-based agentic and generative recommender systems.
(* indicates equal contributions)
All papers@inproceedings{chen2026memrec,
title = {MemRec: Collaborative Memory-Augmented Agentic Recommender System},
author = {Chen, Weixin and Zhao, Yuhan and Huang, Jingyuan and Ye, Zihe and Ju, Clark Mingxuan and Zhao, Tong and Shah, Neil and Chen, Li and Zhang, Yongfeng},
year = 2026,
booktitle = {Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL 2026)}
}
@inproceedings{zhao2026double,
title = {The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation},
author = {Zhao, Yuhan and Chen, Weixin and Chen, Li and Pan, Weike},
year = 2026,
booktitle = {Proceedings of the ACM Web Conference 2026 (WWW '26)}
}
@inproceedings{chen2025leave,
title = {Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users},
author = {Chen, Weixin and Zhao, Yuhan and Chen, Li and Pan, Weike},
year = 2025,
booktitle = {Proceedings of the 19th ACM Conference on Recommender Systems (RecSys'25)},
pages = {226--236}
}
@article{chen2025causality,
title = {Causality-Inspired Fair Representation Learning for Multimodal Recommendation},
author = {Chen, Weixin and Chen, Li and Ni, Yongxin and Zhao, Yuhan},
year = 2025,
journal = {ACM Transactions on Information Systems},
volume = {43},
number = {6},
articleno = {153},
numpages = {29}
}
@article{chen2025investigating,
title = {Investigating User-side fairness in outcome and process for multi-type sensitive attributes in recommendations},
author = {Chen, Weixin and Chen, Li and Zhao, Yuhan},
year = 2025,
journal = {ACM Transactions on Recommender Systems},
volume = {4},
number = {2},
articleno = {25},
numpages = {29}
}
@inproceedings{chen2022global,
title = {Global and personalized graphs for heterogeneous sequential recommendation by learning behavior transitions and user intentions},
author = {Chen, Weixin and He, Mingkai and Ni, Yongxin and Pan, Weike and Chen, Li and Ming, Zhong},
year = 2022,
booktitle = {Proceedings of the 16th ACM Conference on Recommender Systems (RecSys'22)},
pages = {268--277}
}