3 papers
cs.CV2026
DIVER:Diving Deeper into Distilled Data via Expressive Semantic Recovery
Qianxin Xia, Zhiyong Shu, Wenbo Jiang +3
Dataset distillation aims to synthesize a compact proxy dataset that is unreadable or non-raw from the original dataset for privacy protection and highly efficient learning. Howeve…
cs.CV2026
EDITS: Enhancing Dataset Distillation with Implicit Textual Semantics
Qianxin Xia, Jiawei Du, Guoming Lu +2
Dataset distillation aims to synthesize a compact dataset from the original large-scale one, enabling highly efficient learning while preserving competitive model performance. Howe…
cs.CV2026
Efficient Dataset Distillation for Pre-Trained Self-Supervised Models via Statistical Flow Matching
Qianxin Xia, Jiawei Du, Xin Zhang +3
Dataset distillation seeks to synthesize a highly compact dataset that achieves performance comparable to the original dataset on downstream tasks. For the classification task that…