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FIERCE: From Generalist Robot Policies to Fast Specialists via Progress-Failure Feedback
Generalist robot policies offer useful initialization, but refining compact specialists through limited physical interaction requires informative learning feedback. We present FIERCE, a generalist-initialized reinforcement learning framework centered on a unified, task-adaptive progress-failure eval
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