Software Development

Sparse Autoencoder Training

Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.

Publisher / source

Orchestra-Research/AI-Research-SKILLs (found on skills.sh, an awesome list)

Upstream record

Orchestra-Research/AI-Research-SKILLs

Version

Version 2

Published

2026-11-02

Publication review

Approved for publication

Content fingerprint

3af1fa0e513a96c953f4fbd28b1a6cd764fa9c27e512c6f0cfd2b80c2a1706ae