8 citations · 14 across the 7 of their papers we have counts for
4 papers · 1 filter
SAGER: Self-Evolving User Policy Skills for Recommendation Agent
Zhen Tao, Riwei Lai, Chenyun Yu +7
Large language model (LLM) based recommendation agents personalize what they know through evolving per-user semantic memory, yet how they reason remains a universal, static system…
The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
Yuhan Zhao, Weixin Chen, Li Chen +1
Cross-domain recommendation (CDR) offers an effective strategy for improving recommendation quality in a target domain by leveraging auxiliary signals from source domains. Nonethel…
Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation
Weixin Chen, Li Chen, Yuhan Zhao
Despite growing efforts to mitigate unfairness in recommender systems, existing fairness-aware methods typically fix the fairness requirement at training time and provide limited p…
MemRec: Collaborative Memory-Augmented Agentic Recommender System
Weixin Chen, Yuhan Zhao, Jingyuan Huang +6
The evolution of recommender systems has shifted from traditional collaborative filtering to LLM-based agentic systems, which rely on semantic user and item memories to make predic…