isotropic-superposition-model-uniform-spacing

Summary

This model treats each learned feature as a distinct directional arrow in the network's internal space, and because overlapping features interfere with one another, they naturally push apart until they're spread out roughly evenly, like spokes on a wheel. This sets a foundational expectation for how features are arranged, so any downstream reasoning about capacity, interference, or feature independence depends on that even spacing actually holding.