Understanding the inner working functionality of large-scale deep neural
networks is challenging yet crucial in several high-stakes applications.
Mechanistic inter- pretability is an emergent field that tackles this
challenge, often by identifying human-understandable subgraphs in deep neural
networks known as circuits. In vision-pretrained models, these sub