1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.DC2024★ 1 cited
On the Performance and Memory Footprint of Distributed Training: An Empirical Study on Transformers
Zhengxian Lu, Fangyu Wang, Zhiwei Xu +2
Transformer models have emerged as potent solutions to a wide array of multidisciplinary challenges. The deployment of Transformer architectures is significantly hindered by their…
cs.CV2024
ADFQ-ViT: Activation-Distribution-Friendly Post-Training Quantization for Vision Transformers
Yanfeng Jiang, Ning Sun, Xueshuo Xie +2
Vision Transformers (ViTs) have exhibited exceptional performance across diverse computer vision tasks, while their substantial parameter size incurs significantly increased memory…