Aidan Ewart

Mostly my own writing, except for the 'Better Training Methods' section which was written by @Aidan Ewart. We made a lot of progress in 4 months working on Sparse Autoencoders, an unsupervised method to scalably find monosemantic features in LLMs, but there's still plenty of work to do. Below I...

This is a linkpost for Sparse Autoencoders Find Highly Interpretable Directions in Language Models We use a scalable and unsupervised method called Sparse Autoencoders to find interpretable, monosemantic features in real LLMs (Pythia-70M/410M) for both residual stream and MLPs. We showcase monosemantic features, feature replacement for Indirect Object Identification (IOI),...