Publications

@article{chen2026r2qrec,
  title   = {R2QRec: Learning Recommendation Queries from Retrieval Feedback},
  author  = {Chen, Weixin and Liu, Shuchang and Yang, Hailan and Zhao, Yuhan and Kang, Li and Zhang, Xuefeng and Zhang, Chenghao and Wang, Xinyuan and Yang, Hanchen and Wu, Yinghao and Huang, Hua and Bai, Yandong and Yang, Fan and Li, Xiang and Chen, Chunjie and Chen, Li},
  journal = {arXiv preprint arXiv:2610.39984},
  year    = {2026},
  url     = {https://arxiv.org/abs/2610.39984}
}

@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{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)}
}

@inproceedings{tao2026sager,
  title     = {Personalizing How Recommendation Agents Reason: Self-Evolving Per-User Skills for Recommendation Agents},
  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,
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2026},
  pages     = {18438--18460},
  doi       = {10.18653/2026.findings-emnlp.872},
  url       = {https://aclanthology.org/2026.findings-emnlp.872/}
}

@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{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}
}

@article{zhao2026scvug,
  title     = {SC-VUG: Fairness-Aware Cross-Domain Recommendation for Non-Overlapping Users via Sparsity-Calibrated Virtual User Generation},
  author    = {Zhao, Yuhan and Chen, Weixin and Chen, Li and Pan, Weike},
  year      = 2026,
  journal   = {ACM Transactions on Recommender Systems},
  doi       = {10.1145/3841183},
  note      = {Article 3841183}
}

@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}
}

@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}
}

@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},
}