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PoLAR: Factorizing Extent and Mode in Latent Actions for Robot Policy Learning
Robot actions vary in both extent and mode: how much change they produce and what kind of change they produce. A latent action space that reflects this structure may make it easier for downstream policies to map latent actions to robot actions. However, existing latent action methods typically rely
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