2026
Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity
ICML 2026poster
Ensuring the safety of Generative AI requires a nuanced understanding of pluralistic viewpoints. In this paper, we introduce a novel data-driven approach for analyzing ordinal safety ratings in pluralistic settings. Specifically, we address the challenge of interpreting nuanced differences in safety…