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Scouting the Dynamics Gap: Test-Time Policy Adaptation via Action-Outcome Feedback
While pretrained robotic policies exhibit impressive capabilities in controlled environments, unobserved physical properties and dynamics require these policies to rapidly adapt during deployment. Existing test-time adaptation methods typically rely on sparse scalar rewards, failing to exploit the r
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