Weixin Chen

Email: [email protected]

I am currently pursuing my Ph.D. at Hong Kong Baptist University, advised by Prof. Li Chen. From August 2025 to February 2026, I was a Visiting Ph.D. Student at Rutgers University, working with Prof. Yongfeng Zhang. Before my PhD journey, I earned my B.Eng. degree from Shenzhen University in 2020, advised by Prof. Weike Pan.

My current research focuses on agentic and trustworthy recommender systems.

Weixin Chen

Recent News

[2026.05]
MemRec is highlighted as the strongest LLM-based baseline in Meta's MARS paper.
[2026.05]
Paper on diverse cross-domain sequential recommendation (DivCDSR) got accepted by KDD 2026. Congrats to Shu and Yuhan!
[2026.04]
MemRec got accepted by ACL 2026 Main Conference!
[2026.03]
Invited talk on MemRec at Kuaishou, Beijing.
[2026.03]
Invited talk on MemRec at Tencent, Shenzhen.
[2026.01]
Paper on controllable fairness got accepted by WWW 2026 HCRS Workshop as an Oral presentation.
[2026.01]
New preprint on collaborative memory-augmented agentic recommendation is available on arXiv.
[2026.01]
Paper on fairness-aware cross-domain recommendation got accepted by WWW 2026 as co-first author. Congrats to Yuhan!
[2025.09]
Attend RecSys 2025 and present our research work @ Prague. Check our presentation: [Paper] and [Video].
[2025.08]
Happy to join in Rutgers WISE Lab as a visiting student researcher!
[2025.07]
Paper on fairness-aware cross-domain recommendation got accepted by RecSys 2025, as a Spotlight Oral presentation.
[2025.06]
Paper on fairness-aware multimodal recommendation got accepted by TOIS 2025.
[2025.03]
Paper on investigating fairness over different attributes got accepted by TORS 2025.
[2022.09]
Present our research work @ RecSys 2022 remotely. Check our presentation: [Paper] and [Video].
[2022.09]
Start my PhD journey @ HKBU CS.
[2022.06]
Paper on multi-bevhaior sequential recommendation got accepted by RecSys 2022, as an Oral presentation.

Selected Publications

(* indicates equal contributions)

All topics
Total citations: --
MemRec Model
ACL
2026
MemRec: Collaborative Memory-Augmented Agentic Recommender System
W. Chen, Y. Zhao, J. Huang, Z. Ye, C. M. Ju, T. Zhao, N. Shah, L. Chen, Y. Zhang.
ACL 2026 PDF Code Demo BibTeX
🏆 Recognized as "the strongest competitor" among LLM-based methods by Meta's MARS paper.
@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)}
}
DivCDSR Model
KDD
2026
DivCDSR: A Model-Agnostic Framework for Diverse Cross-Domain Sequential Recommendation
S. Chen*, Y. Zhao*, W. Chen, W. Pan, L. Chen.
KDD 2026 BibTeX
@inproceedings{chen2026divcdsr,
  title     = {DivCDSR: A Model-Agnostic Framework for Diverse Cross-Domain Sequential Recommendation},
  author    = {Chen, Shu and Zhao, Yuhan and Chen, Weixin and Pan, Weike and Chen, Li},
  year      = 2026,
  booktitle = {Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '26)}
}
SAGER Model
arXiv
2026
SAGER: Self-Evolving User Policy Skills for Recommendation Agent
Z. Tao, R. Lai, C. Yu, W. Chen, L. Chen, B. Kong, L. Cheng, C. Zhuo, Z. Li, Q. Sun.
arXiv 2026 PDF BibTeX
@article{tao2026sager,
  title   = {SAGER: Self-Evolving User Policy Skills for Recommendation Agent},
  author  = {Tao, Zhen and Lai, Riwei and Yu, Chenyun and Chen, Weixin and Chen, Li and Kong, Beibei and Cheng, Lei and Zhuo, Chengxiang and Li, Zang and Sun, Qingqiang},
  year    = 2026,
  journal = {arXiv preprint arXiv:2604.14972},
  url     = {https://arxiv.org/abs/2604.14972}
}
CDFA Model
WWW
2026
The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
Y. Zhao*, W. Chen*, L. Chen, W. Pan.
WWW 2026 Oral PDF Code BibTeX
@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)}
}
Cofair Model
HCRS@WWW
2026
Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation
W. Chen, L. Chen, Y. Zhao.
WWW 2026 HCRS Workshop Oral PDF Code BibTeX
@inproceedings{chen2026posttraining,
  title     = {Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation},
  author    = {Chen, Weixin and Chen, Li and Zhao, Yuhan},
  year      = 2026,
  booktitle = {Companion Proceedings of the ACM Web Conference}
}
H-Mem Model
EACL
2026
H-Mem: Hybrid Multi-Dimensional Memory Management for Long-Context Conversational Agents
Z. Ye, J. Huang, W. Chen, Y. Zhang.
EACL 2026 PDF BibTeX
@inproceedings{ye2026hmem,
  title     = {H-Mem: Hybrid Multi-Dimensional Memory Management for Long-Context Conversational Agents},
  author    = {Ye, Zihe and Huang, Jingyuan and Chen, Weixin and Zhang, Yongfeng},
  year      = 2026,
  booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (EACL'26)},
  pages     = {7756--7775}
}
VUG Model
RecSys
2025
Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users
W. Chen*, Y. Zhao*, L. Chen, W. Pan.
RecSys 2025 Spotlight Oral PDF Code Slides Poster Video BibTeX
@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}
}
FMMRec Model
TOIS
2025
Causality-Inspired Fair Representation Learning for Multimodal Recommendation
W. Chen, L. Chen, Y. Ni, Y. Zhao.
ACM TOIS PDF Code BibTeX
@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}
}
OtPr Fairness Model
TORS
2025
Investigating User-Side Fairness in Outcome and Process for Multi-Type Sensitive Attributes in Recommendations
W. Chen, Y. Zhao, L. Chen.
ACM TORS PDF Code BibTeX
@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}
}
GPG4HSR Model
RecSys
2022
Global and Personalized Graphs for Heterogeneous Sequential Recommendation by Learning Behavior Transitions and User Intentions
W. Chen, M. He, Y. Ni, W. Pan, Z. Ming, L. Chen.
RecSys 2022 Oral PDF Code Video BibTeX
@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}
}
MRL Model
TIST
2026
Matryoshka Representation Learning for Recommendation with Layer- and Hardness-Adaptive Negative Sampling
R. Lai, L. Chen, W. Chen, R. Chen.
ACM TIST PDF Code BibTeX
@article{lai2026matryoshka,
  title   = {Matryoshka Representation Learning for Recommendation with Layer- and Hardness-Adaptive Negative Sampling},
  author  = {Lai, Riwei and Chen, Li and Chen, Weixin and Chen, Rui},
  year    = 2026,
  journal = {ACM Transactions on Intelligent Systems and Technology},
}

Invited Talks

MemRec
2026
MemRec: Collaborative Memory-Augmented Agentic Recommender System
Kuaishou @ Beijing · Tencent @ Shenzhen

Research Experience

Education

Honors & Awards

Scholarships & Academic Honors

Academic Service

Teaching

(Teaching Assistant)