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DiffCold shatters the seesaw dilemma in item recommendation, enabling accurate cold-start predictions without sacrificing the performance of warm items.
Forget trajectory-level rollouts: MuSEAgent learns faster and reasons better by distilling past interactions into reusable, state-aware decision experiences.
