Addressing Feature Suppression in SAEs — LessWrong

Produced as part of the ML Alignment Theory Scholars Program - Winter 2023-24 Cohort as part of Lee Sharkey's stream. …

x Addressing Feature Suppression in SAEs — LessWrong Sparse Autoencoders (SAEs) Interpretability (ML & AI) AI Frontpage 88 Addressing Feature Suppression in SAEs by Benjamin Wright , Lee Sharkey 16th Feb 2024 AI Alignment Forum 12 min read 5 88 Ω 46 Produced as part of the ML Alignment Theory Scholars Program - Winter 2023-24 Cohort as part of Lee Sharkey's stream. TL;DR Sparse autoencoders are a method of resolving superposition by recovering linearly encoded “features” inside activations. Unfortunately, despite the great recent success of SAEs at extracting human interpretable features, they

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