most citedImproving Global Adversarial Robustness Generalization With Adversarially Trained GAN

6 citations · 6 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021

CLLD: Contrastive Learning with Label Distance for Text Classification

Jinhe Lan, Qingyuan Zhan, Chenhao Jiang +2

Existed pre-trained models have achieved state-of-the-art performance on various text classification tasks. These models have proven to be useful in learning universal language rep…

cs.CV2021★ 6 cited

Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN

Desheng Wang, Weidong Jin, Yunpu Wu +1

Convolutional neural networks (CNNs) have achieved beyond human-level accuracy in the image classification task and are widely deployed in real-world environments. However, CNNs sh…