A Better Concept Map Can Reconstruct Less
TL;DR for operators When inspecting a vision model, the sparse autoencoder that best reconstructs its internal activations may not produce the clearest explanation of what image regions those activations represent. Spatial-SAE addresses a specific modeling limitation: conventional sparse autoencoders do not explicitly coordinate features across neighboring image patches. Its two-stream representation improves concept recovery and spatial alignment in the studied settings, but generally sacrifices reconstruction fidelity. ...