1 citations · 1 across the 8 of their papers we have counts for
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Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training
Mingjia Shi, Yuhao Zhou, Ruiji Yu +8
Vision Mamba has shown close to state of the art performance on computer vision tasks, drawing much interest in increasing it's efficiency. A promising approach is token reduction…
Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios
Kai Wang, Zekai Li, Zhi-Qi Cheng +6
Dataset distillation has demonstrated strong performance on simple datasets like CIFAR, MNIST, and TinyImageNet but struggles to achieve similar results in more complex scenarios.…
Prioritize Alignment in Dataset Distillation
Zekai Li, Ziyao Guo, Wangbo Zhao +8
Dataset Distillation aims to compress a large dataset into a significantly more compact, synthetic one without compromising the performance of the trained models. To achieve this,…
A Closer Look at Time Steps is Worthy of Triple Speed-Up for Diffusion Model Training
Kai Wang, Mingjia Shi, Yukun Zhou +6
Training diffusion models is always a computation-intensive task. In this paper, we introduce a novel speed-up method for diffusion model training, called, which is based on a clos…