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TurnOPD redefines on-policy distillation by optimizing training budgets at the turn level, leading to superior agent performance without increasing training time.
Current AI research in education overlooks the critical sociocultural dimension of learner agency, risking a narrow focus in AI-mediated learning environments.
Current video world models may look good on the surface, but they fail to handle critical reasoning tasks, revealing a gap in trustworthiness that could jeopardize robotic manipulation safety.
Even high-performing Vid-LLMs can be easily misled into retracting correct judgments and fabricating justifications under adversarial feedback.
