dailyai.report

A new exploratory project uses a black-box LLM autorater to extract 10-20 distinct features from model transcripts. Researchers split data into user turns, thoughts, and responses to identify novel behaviors. This method helps AI Alignment practitioners find surprising correlations in training distributions. It offers a qualitative shortcut for auditing target models during deployment.