SynthAgent: Adapting Web Agents with Synthetic Supervision

ArXi:2511.06101v3 Announce Type: replace-cross Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and nstrations. Recent works have explored synthetic data generation to address this challenge, however, they suffer from data quality issues where synthesized tasks contain hallucinations that cannot be executed, and collected trajectories are noisy with redundant or misaligned actions.