TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization

20 March 2023

Papers citing "TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization"

4 / 4 papers shown

Title
An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation Ziquan Liu Yi Tian Xu Yuanhong Xu Qi Qian Hao Li Rong Jin Xiangyang Ji Antoni B. Chan OOD 27 14 0 25 May 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 170 256 0 10 Nov 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 44 100 0 07 Oct 2021