VeriCUA: Verification as Agentic Exploration for Computer-Using Agents
[Sztuczna inteligencja] Autorzy: Qiushi Sun, Da Yu, Alexander Knop i 5 więcej
Building and scaling computer-using agents (CUAs) across desktop, mobile, and web environments requires reliable task-completion verification for data curation, evaluation, and reinforcement learning. Typical automated approaches prompt vision-language models (VLMs) to judge trajectories or generate programs to inspect application state. However, both rely on partial views of complex digital environments. VLM judges are restricted to supplied observations, while generated programs depend on accessible state. These views can omit decisive evidence or leave completion judgments unsupported. Tailoring separate verifiers to different platforms and access settings adds further engineering cost. We present VeriCUA, a platform-agnostic framework for verification through agentic exploration. It treats verification as dynamic evidence gathering and assessment within a shared procedure for online…
- Kategoria arxiv
- cs.AI
- Kategoria
- Sztuczna inteligencja