8 citations · 9 across the 7 of their papers we have counts for
4 papers · 1 filter
Beyond Static LLM Policies: Imitation-Enhanced Reinforcement Learning for Recommendation
Yi Zhang, Lili Xie, Ruihong Qiu +2
Recommender systems (RecSys) have become critical tools for enhancing user engagement by delivering personalized content across diverse digital platforms. Recent advancements in la…
MARCO: A Cooperative Knowledge Transfer Framework for Personalized Cross-domain Recommendations
Lili Xie, Yi Zhang, Ruihong Qiu +2
Recommender systems frequently encounter data sparsity issues, particularly when addressing cold-start scenarios involving new users or items. Multi-source cross-domain recommendat…
DARLR: Dual-Agent Offline Reinforcement Learning for Recommender Systems with Dynamic Reward
Yi Zhang, Ruihong Qiu, Xuwei Xu +2
Model-based offline reinforcement learning (RL) has emerged as a promising approach for recommender systems, enabling effective policy learning by interacting with frozen world mod…
ROLeR: Effective Reward Shaping in Offline Reinforcement Learning for Recommender Systems
Yi Zhang, Ruihong Qiu, Jiajun Liu +1
Offline reinforcement learning (RL) is an effective tool for real-world recommender systems with its capacity to model the dynamic interest of users and its interactive nature. Mos…