Efficient Dataset Distillation for Pre-Trained Self-Supervised Models via Statistical Flow Matching

Dataset distillation seeks to synthesize a compact surrogate dataset that enables performance comparable to training on the original dataset for downstream tasks. For the scenario where pre-trained self-supervised models serve as priors, traditional Linear Gradient Matching optimizes synthetic image