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#recommender-systems

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DAY 01Wednesday JUN 24 · 20261 SUMMARIES
arXiv cs.AIAI & LLMs

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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