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Annotations can be transformed into powerful oracle rollouts, dramatically enhancing the efficiency of reinforcement learning for video MLLMs.
Behavior-derived rewards enable MLLMs to generate effective recommendations without user-specific data at inference, outperforming traditional methods.
