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An independent researcher dissects a single 1×1 convolutional neuron in InceptionV1, using Hadamard product clustering to reveal detection patterns and discovers how gradient descent hides concepts in noise.

Block-sparse featurizers remap dense vision model activations into block-sparse representations, making the internal feature spaces of ViT, CNN, and other models readable and interpretable. This article explores their core principles, links to mechanistic interpretability, and applications.