Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers
SAGE (Selective Agent Guidance via Entropy), a framework that queries a VLM only when the learner is uncertain, executes the suggested action during training, and distills guidance into a lightweight Reinforcement Learning policy, is proposed.
Giovanni Bonetta, Matteo Merler, Davide Zago et al.
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