12 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
Sample-wise Adaptive Weighting for Transfer Consistency in Adversarial Distillation
Hongsin Lee, Hye Won Chung
Adversarial distillation in the standard min-max adversarial training framework aims to transfer adversarial robustness from a large, robust teacher network to a compact student. H…
SNAP: Low-Latency Test-Time Adaptation with Sparse Updates
Hyeongheon Cha, Dong Min Kim, Hye Won Chung +2
Test-Time Adaptation (TTA) adjusts models using unlabeled test data to handle dynamic distribution shifts. However, existing methods rely on frequent adaptation and high computatio…
CovMatch: Cross-Covariance Guided Multimodal Dataset Distillation with Trainable Text Encoder
Yongmin Lee, Hye Won Chung
Multimodal dataset distillation aims to synthesize a small set of image-text pairs that enables efficient training of large-scale vision-language models. While dataset distillation…
VIPAMIN: Visual Prompt Initialization via Embedding Selection and Subspace Expansion
Jaekyun Park, Hye Won Chung
In the era of large-scale foundation models, fully fine-tuning pretrained networks for each downstream task is often prohibitively resource-intensive. Prompt tuning offers a lightw…