Legible Networks: recasting neural nets so you can read them exactly

A new interpretability method called Legible Networks recasts trained neural networks into a geometry that allows exact reading with arithmetic. The author claims this is the exact counterpart of Anthropic's averaged J-lens and includes the first measurement of how lossy averaged lenses actually are. This represents a concrete advance in AI interpretability by moving from averaged approximations to exact representations.