Unifying Dataset Pruning and Distillation for Efficient Large-scale Compression 事件

Unifying Dataset Pruning and Distillation for Efficient Large-scale Compression arXiv:2502.06434v2 Announce Type: replace Abstract: Dataset pruning (DP) and dataset distillation (DD) fundamentally differ in their outputs: DP selects original image subsets, while DD generates synthetic images. Recently, DD's increasing reliance on original images suggests a convergence of the two directions. To investigate this convergence trend, we propose a unified dataset compression (DC) benchmark. This benc