Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation

Recommender systems often induce filter bubbles and semantic homogenization by monolithically optimizing for immediate user engagement. Standard single-objective models, including traditional Deep Q-Networks, are ill-equipped to navigate the trade-offs between platform retention and critical societa…

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