Sharkey, Lee

8 publications

ICLR 2025 Bilinear MLPs Enable Weight-Based Mechanistic Interpretability Michael T Pearce, Thomas Dooms, Alice Rigg, Jose Oramas, Lee Sharkey

TMLR 2025 Open Problems in Mechanistic Interpretability Lee Sharkey, Bilal Chughtai, Joshua Batson, Jack Lindsey, Jeffrey Wu, Lucius Bushnaq, Nicholas Goldowsky-Dill, Stefan Heimersheim, Alejandro Ortega, Joseph Isaac Bloom, Stella Biderman, Adrià Garriga-Alonso, Arthur Conmy, Neel Nanda, Jessica Mary Rumbelow, Martin Wattenberg, Nandi Schoots, Joseph Miller, William Saunders, Eric J Michaud, Stephen Casper, Max Tegmark, David Bau, Eric Todd, Atticus Geiger, Mor Geva, Jesse Hoogland, Daniel Murfet, Thomas McGrath

ICLR 2025 Sparse Autoencoders Do Not Find Canonical Units of Analysis Patrick Leask, Bart Bussmann, Michael T Pearce, Joseph Isaac Bloom, Curt Tigges, Noura Al Moubayed, Lee Sharkey, Neel Nanda

NeurIPS 2024 Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning Dan Braun, Jordan Taylor, Nicholas Goldowsky-Dill, Lee Sharkey

ICMLW 2024 Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning Dan Braun, Jordan Taylor, Nicholas Goldowsky-Dill, Lee Sharkey

NeurIPSW 2024 Interpretability as Compression: Reconsidering SAE Explanations of Neural Activations Kola Ayonrinde, Michael T Pearce, Lee Sharkey

NeurIPSW 2024 Interpretability as Compression: Reconsidering SAE Explanations of Neural Activations Kola Ayonrinde, Michael T Pearce, Lee Sharkey

ICLR 2024 Sparse Autoencoders Find Highly Interpretable Features in Language Models Robert Huben, Hoagy Cunningham, Logan Riggs Smith, Aidan Ewart, Lee Sharkey