Frontier LLMs pass fewer than 58% of systematically varied safety-fact scenarios, revealing weak generalization of critical safety knowledge to naive user queries.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
dataset 1
citation-polarity summary
fields
cs.AI 1years
2025 1verdicts
CONDITIONAL 1roles
dataset 1polarities
use dataset 1representative citing papers
citing papers explorer
-
SAGE-Eval: Evaluating LLMs for Systematic Generalizations of Safety Facts
Frontier LLMs pass fewer than 58% of systematically varied safety-fact scenarios, revealing weak generalization of critical safety knowledge to naive user queries.