MUSE decouples reconstruction and semantic learning in visual tokenization via topological orthogonality, yielding SOTA generation quality and improved semantic performance over its teacher model.
Emerging properties in self-supervised vision transformers
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Representations learned by large AI models are converging toward a shared statistical model of reality.
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MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
MUSE decouples reconstruction and semantic learning in visual tokenization via topological orthogonality, yielding SOTA generation quality and improved semantic performance over its teacher model.
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The Platonic Representation Hypothesis
Representations learned by large AI models are converging toward a shared statistical model of reality.