ProRe uses reasoner-actor collaboration for proactive state probing to assign accurate rewards to GUI agents, improving accuracy by 5.3% and policy success rates by 22.4% on over 3K trajectories.
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ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
ProRe uses reasoner-actor collaboration for proactive state probing to assign accurate rewards to GUI agents, improving accuracy by 5.3% and policy success rates by 22.4% on over 3K trajectories.