Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajectory satisfies the success criteria implied by the user instruction. Existing GUI reward verifiers, however, often under-specify how these criteria should be constructed...
Tao Xiong, Xavier Hu, Wen-Kai Wang et al.· 1 citation
gui-PRA is introduced, a Process Reward Agent that transforms GUI process evaluation from passive scoring into active investigation, and demonstrates strong competitiveness against fully trained critic models.
Tao Xiong, Xavier Hu, Yurun Chen et al.· arXiv.org· 5 citations
GSAR (Goal-State-Anchor Reward), a RL reward framework that supports scalable task generation and delivers reliable reward signals for stable and efficient policy optimization, is introduced.
Long Zhang, Yuhan Chen, Chaoran Zhang et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.