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cs.CV2025
Hard Labels In! Rethinking the Role of Hard Labels in Mitigating Local Semantic Drift
Jiacheng Cui, Bingkui Tong, Xinyue Bi +3
Soft labels from teacher models are a de facto practice for knowledge transfer and large-scale dataset distillation (e.g., SRe2L, LPLD). However, when we limit the number of crops…
cs.CV2025
FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation
Jiacheng Cui, Xinyue Bi, Yaxin Luo +3
Residual connection has been extensively studied and widely applied at the model architecture level. However, its potential in the more challenging data-centric approaches remains…
cs.CV2025
Dataset Distillation via Committee Voting
Jiacheng Cui, Zhaoyi Li, Xiaochen Ma +3
Dataset distillation aims to synthesize a compact yet representative dataset that preserves the essential characteristics of the original data for efficient model training. Existin…