Safety3h ago
Safety
LLM-Driven Feature Discovery For Model Behavior
A new exploratory project uses black-box LLM autoraters to extract 10-20 distinct features from model transcripts. Researchers split data into user turns, thoughts, and responses to identify novel behaviors and correlations. This method streamlines qualitative analysis of RL training and evals. It provides AI safety practitioners a faster way to map target model distributions.