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OnlineWM: Causality-Aware Active Online Learning for Effective World Modeling
Generative world models aim to predict future states conditioned on actions, where action controllability is fundamental for reliable dynamics modeling. While recent efforts leverage simulator-generated data to enhance this capability, existing training pipelines face two fundamental limitations. Fi
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