#recommender-systems
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Tag · #recommender-systems
Stochastic Primal-Dual Decoding for Generative Recommender Systems
The paper introduces a stochastic primal-dual decoding framework to balance competing objectives in generative recommender systems, ensuring constraints are met during inference without retraining the model.
arXiv cs.AI
Breaking Filter Bubbles with Semantic Pareto-DQN
A new reinforcement learning framework for recommender systems that treats engagement, diversity, and fairness as distinct, non-aggregable rewards to prevent semantic homogenization.
arXiv cs.AI
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