AI RESEARCH
A Generalized Singular Value Theory for Neural Networks
arXiv CS.AI
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ArXi:2605.06938v1 Announce Type: cross Building on the abstract Generalized Singular Value Decomposition (GSVD) theory of Brown, we prove that most modern neural architectures admit a generalized SVD representation in which they are left-invertible before a final linear layer, with no change in input-output behavior.