Fairness Begins with State: Purifying Latent Preferences for Hierarchical Reinforcement Learning in Interactive Recommendation
arXiv:2603.03820v1 Announce Type: new Abstract: Interactive recommender systems (IRS) are increasingly optimized with Reinforcement Learning (RL) to capture the sequential nature of user-system dynamics. However, …
Yun Lu, Xiaoyu Shi, Hong Xie, Xiangyu Zhao, Mingsheng Shang
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