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Elana Simon

@elanasimon.bsky.social
382 followers 10 following 9 posts
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Elana Simon @elanasimon.bsky.social · 19/11/2024
🧬 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)
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Reposted by Elana Simon
Anshul Kundaje @anshulkundaje.bsky.social · 19/11/2024
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
biorxiv.org
InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders
Protein language models (PLMs) have demonstrated remarkable success in protein modeling and design, yet their internal mechanisms for predicting structure and function remain poorly understood. Here w...
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Reposted by Elana Simon
Kevin K. Yang 楊凱筌 @kevinkaichuang.bsky.social · 18/11/2024
Mechanistic interpretability on a protein language model www.biorxiv.org/content/10.1...
Overview of SAE methodology and representative SAE features revealed through automated activation
pattern analysisUsing mechanistic interpretability to steer generationsSAE feature analysis and visualizations reveal features with diverse and consistent activation patterns
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