LLM-DRIVEN FEATURE DISCOVERY

Summary from the TLDR Dev newsletter

LLM-driven feature discovery involves analyzing a dataset of chat transcripts to generate and cluster features related to model behavior. The method, which does not require access to model internals, identifies high-level features and predicts some aspects of the model's responses based on user input, although prediction accuracy is limited.