When Pruning Meets Interpretability: Preserving Sparse Autoencoder Robustness in LLMs

Suchit Gupte, Xueru Zhang, Mohammad Mahdi Khalili

Sparse autoencoders (SAEs) are widely used to interpret the internal representations of large language models (LLMs), yet their reliability under post-hoc model compression remains…