3 papers
cs.IR2026
Proactive Guiding Strategy for Item-side Fairness in Interactive Recommendation
Chongjun Xia, Xiaoyu Shi, Hong Xie +3
Item-side fairness is crucial for ensuring the fair exposure of long-tail items in interactive recommender systems. Existing approaches promote the exposure of long-tail items by d…
cs.IR2026
LLM-Enhanced Reinforcement Learning for Long-Term User Satisfaction in Interactive Recommendation
Chongjun Xia, Yanchun Peng, Xianzhi Wang
Interactive recommender systems can dynamically adapt to user feedback, but often suffer from content homogeneity and filter bubble effects due to overfitting short-term user prefe…
cs.AI2025
Revisiting Fairness-aware Interactive Recommendation: Item Lifecycle as a Control Knob
Yun Lu, Xiaoyu Shi, Hong Xie +3
This paper revisits fairness-aware interactive recommendation (e.g., TikTok, KuaiShou) by introducing a novel control knob, i.e., the lifecycle of items. We make threefold contribu…