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On-policy distillation can boost task success rates in world action models by leveraging teacher supervision on student-generated histories, achieving up to 58.3% success in complex tasks.
A frozen policy can achieve up to 86% success in manipulation tasks through guided inference, underscoring the power of learned critics in real-time decision-making.