LLM Safety Judges Stick to Rigid Priors, Missing Contextual Nuance
A systematic study shows that large language models used as safety judges struggle to incorporate new contextual information or altered safety definitions, often defaulting to their built‑in priors. This rigidity limits their reliability for nuanced, scalable safety assessments across diverse scenarios.