SAEs

Inference-Time Decomposition of Activations (ITDA): A Scalable Approach to Interpreting Large Language Models

ITDA LLMs SAEs Mechanistic Interpretability Representations Model Diffing

Patrick Leask, Noura Al Moubayed, and Neel Nanda debut ITDA—a new mechanistic interpretability approach 100x faster to train than SAEs—at ICML'25

Sparse Autoencoders Do Not Find Canonical Units of Analysis

SAEs Mechanistic Interpretability Representations

Patrick Leask and Noura Al Moubayed present a paper and poster on SAEs at ICLR'25

Calendar feature geometry in GPT-2 layer 8 residual stream SAEs

LLMs SAEs GPT2 Geometry

Patrick Leask, Bart Bussmann, and Neel Nanda take a close look at GPT-2’s SAE feature geometry on the AI Alignment Forum