dailyai.report

A new exploratory project uses a black-box LLM autorater to identify 10-20 key features within model transcripts. The system splits data into user turns, thoughts, and responses to isolate specific behaviors. This method helps researchers find surprising correlations in RL training and evaluation sets. It streamlines how AI alignment teams audit complex model distributions.