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News/Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation
arxiv
PublishedJune 25, 2026 at 4:00 AM
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Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation

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arXiv:2606.24042v1 Announce Type: new Abstract: 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

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