Global and Personalized Graphs for Heterogeneous Sequential Recommendation by Learning Behavior Transitions and User Intentions. - Weixin Chen 001; Mingkai He; Yongxin Ni; Weike Pan; Li Chen 009; Zhong Ming 001 (RecSys, 2022)

FMMRec: Fairness-aware Multimodal Recommendation. - Weixin Chen 001; Li Chen 009; Yongxin Ni; Yuhan Zhao 001; Fajie Yuan; Yongfeng Zhang 003 (CoRR, 2023)

Matryoshka Representation Learning for Recommendation. - Riwei Lai; Li Chen 009; Weixin Chen 001; Rui Chen 012 (CoRR, 2024)

Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users. - Weixin Chen 001; Yuhan Zhao 001; Li Chen 009; Weike Pan (RecSys, 2025)

Causality-Inspired Fair Representation Learning for Multimodal Recommendation. - Weixin Chen 001; Li Chen 009; Yongxin Ni; Yuhan Zhao 001 (ACM Trans. Inf. Syst., 2025)

Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation. - Weixin Chen 001; Li Chen 009; Yuhan Zhao 001 (WWW (Companion Volume), 2026)

The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation. - Yuhan Zhao 001; Weixin Chen 001; Li Chen 009; Weike Pan (WWW, 2026)

Investigating User-Side Fairness in Outcome and Process for Multi-Type Sensitive Attributes in Recommendations. - Weixin Chen 001; Li Chen 009; Yuhan Zhao 001 (Trans. Recomm. Syst., 2026)