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Yangyang Kang

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Preprint Sep 2026

World Model-Guided Reinforcement Learning via Counterfactual User Engagement Simulation

Reinforcement learning for user-centric agents is limited by the cost, latency, and risk of collecting online feedback, as well as by the lack of counterfactual comparisons under the same user state. In this paper, we propose World Model-Guided Reinforcement Learning via counterfactual user engagement simulation (WMG-R...

Ang Li, Xin Xu, Bin Liang et al. · 0 citations

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