Foundations of Neuron-level Interpretability: Automation, Evaluation and Training

Despite the impressive performance of deep neural networks, our understanding of how they work is very limited. To address this, the field of mechanistic interpretability aims to build a bottom-up understanding of the mechanisms that a neural network uses to calculate its output. An important buildi