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Cross-device agents struggle significantly, with top performers only managing a 12.5% success rate in executing complex, multi-device tasks.
By explicitly modeling and calibrating a model's intrinsic uncertainty, EGPO unlocks significant gains in reasoning performance for RL-trained language models.
