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LLMs Automate Feature Discovery in Model Transcripts
A new exploratory project uses a black box LLM autorater to extract 10-20 qualitative features from model transcripts. Researchers split data into user turns, thoughts, and responses to identify novel behaviors. This method helps AI Alignment teams find surprising correlations in training distributions. It offers a scalable way to audit target models without manual review.