Monitoring Web Agents Without Internal Signals: Observable Trajectories and Key-Step Supervision

Explain Like I'm Normal

Researchers developed a way to predict if a web agent is failing without needing access to the model's inner thoughts or confidence levels. By analyzing 'macro' behavior patterns and 'micro' consistency checks through repeated queries, they can spot the exact moment an agent goes off the rails. This allows developers to monitor black-box models like GPT-4 or Claude 3.5 without relying on expensive internal logit access.