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A new graphical notation reveals the inner workings of interpretable AI architectures, translating complex designs into clear, reproducible PyTorch code.
A unified theory of interpretability that leverages Lagrangian mechanics to transform opaque models into interpretable ones, revealing new research avenues and design principles.
