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ResMerge: Residual Policy Learning and Merging for Continual Adaptation of Pre-trained Robot Policies

ResMerge proposes a two-stage framework that learns mergeable residual policies atop a frozen pre-trained policy: residual reinforcement learning obtains task-specific corrections during adaptation without additional expert demonstrations, while parameter-space merging consolidates compatible residuals to reduce stored parameters.

Part of the event: ResMerge: Residual Policy Learning and Merging for Continual Adaptation

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