MGPO: Manifold-Guided Diffusion Alignment for Task-Aware Dataset Distillation

Excerpt

arXiv:2610.05252v1 Announce Type: cross Abstract: Diffusion-based dataset distillation (DD) suffers from a fundamental objective mismatch: likelihood-driven diffusion models prioritize density approximation over the discriminative decision boundaries required for downstream tasks. Beyond semantic mismatch, relying solely on density also leads to geometric coverage loss, where generated samples collapse into a few high-density modes and fail to cover the manifold's structural diversity. We propos