Causal Circuit

A core concept in mechanistic interpretability that describes the computational structure of a neural network. A causal circuit refers to the minimal causal computational structure—comprising attention heads, MLP layers, and information flow pathways—required to reproduce a specific model behavior. Circuit size reflects the difficulty of reverse-engineering that behavior.