EnvOS: Auditing Computer-Use Agents When the World Moves On : Phenomenon-Based Task Construction, Certification, and Evidence-Based Evaluation

EnvOS is a framework that audits computer‑use agents operating in dynamic software environments, ensuring that mid‑task changes fire correctly, tasks remain solvable, and grading is accurate. It verifies these conditions before and after agent runs, using archived evidence to re‑check verdicts. Applied to stale‑information scenarios, EnvOS revealed significant performance gaps for large language models, highlighting how unseen updates can derail agent behavior.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• llms
• agents
• reinforcement-learning