dailyai.report

A new exploratory project uses black-box LLM autoraters to extract 10-20 qualitative features from model transcripts. By splitting data into user turns, thoughts, and responses, researchers identify novel behaviors and correlations. This method provides a scalable way for AI safety practitioners to audit target models in deployment or RL training.