Bahareh Tolooshams

Geometric overlap alone misrepresents feature interference in sparse autoencoders; realized cross-talk is heavily governed by activation statistics and actively steered by architectural levers like bias compensation and encoder-decoder decoupling.

Statistically independent factors can exhibit anisotropic behavior that traditional methods fail to capture, revealing deeper complexities in representation learning.