3 papers
cs.LG2025
Efficient Skill Discovery via Regret-Aware Optimization
He Zhang, Ming Zhou, Shaopeng Zhai +2
Unsupervised skill discovery aims to learn diverse and distinguishable behaviors in open-ended reinforcement learning. For existing methods, they focus on improving diversity throu…
cs.IR2025
Improving Recommendation Fairness without Sensitive Attributes Using Multi-Persona LLMs
Haoran Xin, Ying Sun, Chao Wang +3
Despite the success of recommender systems in alleviating information overload, fairness issues have raised concerns in recent years, potentially leading to unequal treatment for c…
cs.IR2025
LLMs as Better Recommenders with Natural Language Collaborative Signals: A Self-Assessing Retrieval Approach
Haoran Xin, Ying Sun, Chao Wang +2
Incorporating collaborative information (CI) effectively is crucial for leveraging LLMs in recommendation tasks. Existing approaches often encode CI using soft tokens or abstract i…