Sree Nitya Kollu

Hazard or Anomaly? Evaluating VLMs for Understanding Dangers and Discrepancies

This work evaluates several state-of-the-art VLMs across two datasets and multiple prompting strategies to test whether an explicit distinction between hazard and anomaly changes model behavior, and shows that explicitly separating anomaly from hazard provides a more informative evaluation of VLM safety reasoning and exposes failure modes that binary safety judgments can obscure.