AI RESEARCH
The Universal Normal Embedding
arXiv CS.CV
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ArXi:2603.21786v1 Announce Type: new Generative models and vision encoders have largely advanced on separate tracks, optimized for different goals and grounded in different mathematical principles. Yet, they share a fundamental property: latent space Gaussianity. Generative models map Gaussian noise to images, while encoders map images to semantic embeddings whose coordinates empirically behave as Gaussian.