Tejaswini Pedapati

Preliminary results reveal substantial differences in safety-utility calibration across models and show that failures can emerge only after several initially safe interaction steps, motivating treating agent safety as a trajectory-level property rather than a single-turn or binary success criterion.

Forget retraining: probing intermediate layer embedding sensitivity offers a surprisingly effective and efficient way to spot AI-generated images.