Interpreting Attention Layer Outputs with Sparse Autoencoders. - Connor Kissane; Robert Krzyzanowski; Joseph Isaac Bloom; Arthur Conmy; Neel Nanda (CoRR, 2024)

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 (ICLR, 2025)

Open Problems in Mechanistic Interpretability. - Lee Sharkey; Bilal Chughtai; Joshua Batson; Jack Lindsey; Jeff Wu 003; Lucius Bushnaq; Nicholas Goldowsky-Dill; Stefan Heimersheim; Alejandro Ortega; Joseph Isaac Bloom; Stella Biderman; Adrià Garriga-Alonso; et al. (CoRR, 2025)

SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability. - Adam Karvonen; Can Rager; Johnny Lin; Curt Tigges; Joseph Isaac Bloom; David Chanin; Yeu-Tong Lau; Eoin Farrell; Callum McDougall; Kola Ayonrinde; Matthew Wearden; Arthur Conmy; et al. (CoRR, 2025)

ContextBench: Modifying Contexts for Targeted Latent Activation. - Robert Graham; Edward Stevinson; Leo Richter; Alexander Chia; Joseph Miller; Joseph Isaac Bloom (CoRR, 2025)