A geometry-aware dataset condensation technique reformulates subset selection as one-sided partial optimal transport alignment plus regularization to improve diffusion model training fidelity.
A survey on dataset distillation: Approaches, applications and future directions
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HoPA captures high-order cross-modal alignments via a shared proxy to enable scalable omnimodal dataset distillation with better performance-compression trade-offs.
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Geometry-Aware Dataset Condensation for Diffusion Model Training
A geometry-aware dataset condensation technique reformulates subset selection as one-sided partial optimal transport alignment plus regularization to improve diffusion model training fidelity.
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Omnimodal Dataset Distillation via High-order Proxy Alignment
HoPA captures high-order cross-modal alignments via a shared proxy to enable scalable omnimodal dataset distillation with better performance-compression trade-offs.