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Found 2 papers, 2 papers with code
Self-supervised Dataset Distillation: A Good Compression Is All You Need
In this work, we consider addressing this task through the new lens of model informativeness in the compression stage on the original dataset pretraining.
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching
We call this perspective "generalized matching" and propose Generalized Various Backbone and Statistical Matching (G-VBSM) in this work, which aims to create a synthetic dataset with densities, ensuring consistency with the complete dataset across various backbones, layers, and statistics.
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