AINeutralarXiv – CS AI · May 127/10
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Flag Varieties: A Geometric Framework for Deep Network Alignment
Researchers establish a unified geometric framework using flag varieties to explain alignment phenomena in deep neural networks, proving that subspace intersection dimension is the fundamental observable governing how weight matrices organize themselves. The work provides theoretical foundations for previously empirical observations about gradient flow, Neural Collapse, and representation similarity, with implications for understanding how neural networks learn.