arxiv
PublishedJuly 2, 2026 at 4:00 AM
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Warp RL: Reshaping Base Policy Distributions for Dynamics Adaptation
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arXiv:2606.31043v2 Announce Type: replace Abstract: Residual reinforcement learning adapts a pretrained robot policy by learning an additive correction to its actions. While effective when adaptation amounts to shifting the base policy's action distribution, additive corrections cannot change the di
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Originally published on arxiv ↗