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About this paper
Soheun Yi, Yizhou Lu, Chandler Squires, Pradeep Ravikumar
The paper develops conditional latent variable models that factor generation into an attribute-indexed concept distribution and feature-generation process. Under stated conditions, matching observed feature distributions implies a constrained latent transition, with identifiability only up to an allowed transition group. Extrapolation to unseen attributes requires transported attribute-potential identities; affine structure can provide this link, but unrestricted indexing can change unseen laws.
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