Author

Yang Wan

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Jul 2026

SeekJudge: A Practical Reward Framework for Reinforcement Learning in Computer-Use Agents

The proposed SeekJudge framework, in which four role-specialized agents, a Condense, a Ground, a Seek and an Analyze agent, reach a verdict through a Seek--Analyze loop over the trajectory, is the first practical model-based reward to match or surpass native rule-based supervision in online RL.

Yang Wan, Zhenhao Zhang, Jie-Rui Wang et al. · arXiv.org · 0 citations