SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization
SAEVerbalizer is introduced, a framework that injects SAE decoder directions into an LLM's representations and fine-tunes the LLM's downstream layers to generate natural-language explanations of the injected features.