Fairness Begins with State: Purifying Latent Preferences for Hierarchical Reinforcement Learning in Interactive Recommendation

Fairness Begins with State: Purifying Latent Preferences for Hierarchical Reinforcement Learning in Interactive Recommendation explores Develop a fairness-oriented interactive recommendation system leveraging denoised latent preferences and hierarchical decision-making.. Commercial viability score: 4/10 in Recommender Systems.