dailyai.report

A new exploratory project uses black-box LLM autoraters to identify 10-20 distinct features within model transcripts. The method splits data into user turns, thoughts, and responses to uncover hidden correlations. This approach helps AI Alignment Forum researchers find novel behaviors. It provides a qualitative lens for auditing RL training and evaluation distributions.