dailyai.report

A new exploratory project uses black box LLMs to extract 10-20 qualitative features from model transcripts. The method splits data into user turns, thoughts, and responses to identify novel behaviors. This approach helps researchers find surprising correlations in deployment distributions. It provides a scalable way to audit model internals without manual labeling.