Back to News
Partnership2026-04-17
ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration
Source: Arxiv CS.AI
arXiv:2509.21823v2 Announce Type: replace Abstract: Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods struggle to generalize to GUI agents, where access to ground-truth trajectories or application databases...
arxivpapersagents