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Supervise What Decides Success: Criterion-Aligned Auxiliary Losses for Latent World-Model Planning
Latent world models plan by scoring candidate action sequences with distances in latent space. However, task success is judged by physical quantities, which we call the success-criterion quantities. In all four latent world models we examine, the end-effector position is encoded in the latent state
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