🧬 What are protein language models (PLMs) actually learning about biology? Our paper introduces InterPLM - a framework that reveals interpretable features in PLMs using sparse autoencoders, giving us a window into how these models represent protein structure and function. 🧵(1/8)

www.biorxiv.org/content/10.1... InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders Code: github.com/ElanaPearl/I... Interactive site: interplm.ai Nice work by Elana Simon from James Zou lab

Mechanistic interpretability on a protein language model www.biorxiv.org/content/10.1...