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TuringViT outperforms leading ViT models with just 10% of the training data, making state-of-the-art vision technology accessible to a wider audience.
Jointly optimizing dimensionality reduction and clustering on a manifold yields state-of-the-art clustering performance, even surpassing established algorithms.
