2025
Low-Rank Adapting Models for Sparse Autoencoders
ICML 2025poster
Sparse autoencoders (SAEs) aim to decompose language model representations into a sparse set of linear latent vectors. Recent works have improved SAEs using language model gradients, but these techniques require many expensive backward passes during training and still cause a significant increase in…