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Yongmin Lee

2 accepted papers

2025

CovMatch: Cross-Covariance Guided Multimodal Dataset Distillation with Trainable Text Encoder

NeurIPS 2025poster

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 has shown promise in unimodal tasks, extending it to multimodal contrastive learning presents key challenges: learning…

Cited by 0SourceScholar
2024

SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching

ICML 2024poster

Dataset distillation aims to synthesize a small number of images per class (IPC) from a large dataset to approximate full dataset training with minimal performance loss. While effective in very small IPC ranges, many distillation methods become less effective, even underperforming random sample sele…

Cited by 9SourcePDFScholar