一作ACL 2026Poster· Natural Language Processing
Constructing Interpretable Features from Compositional Neuron Groups
Or David Shafran · Atticus Geiger · Mor Geva
摘要
A central goal for mechanistic interpretability has been to identify the right units of analysis in large language models (LLMs) that causally explain their outputs. While early work focused on individual neurons, evidence that neurons often encode multiple concepts has motivated a shift toward a...