Circuit Analysis
A method in mechanistic interpretability that traces the collaborative pathways of components such as attention heads and MLPs to understand the computational mechanisms underlying specific behaviors of neural networks.
Timeline (last 90 days)
Current mainstream interpretability approaches include post-hoc attribution methods (such as attention visualization, SHAP) and mechanistic interpretability (such as sparse autoencoders, circuit analysis), with the latter attempting to locate identifiable "feature circuits" at the level of neuron activations.
Circuit analysis (such as tracing the collaborative paths of attention heads and MLPs) is still effective, but what it explains is the computation path, not the 'cleanliness' of the representation space; the two belong to different levels of questions.
All Facts (2)
Current mainstream interpretability approaches include post-hoc attribution methods (such as attention visualization, SHAP) and mechanistic interpretability (such as sparse autoencoders, circuit analysis), with the latter attempting to locate identifiable "feature circuits" at the level of neuron activations.
50%UnverifiedCircuit analysis (such as tracing the collaborative paths of attention heads and MLPs) is still effective, but what it explains is the computation path, not the 'cleanliness' of the representation space; the two belong to different levels of questions.
50%