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Our research aims to unify existing works' diverging opinions on how architectural components affect the adversarial robustness of CNNs.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2017
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Paulius Micikevicius, Sharan Narang, Jonah Alben, Gregory Diamos, Erich Elsen, David Garcia, Boris Ginsburg, Michael Houston, Oleksii Kuchaiev, Ganesh Venkatesh, et al · 2017
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Cyclical learning rates for training neural networks
Leslie N Smith · 2017
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L2 regularization versus batch and weight normalization
Twan Van Laarhoven · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Mma training: Direct input space margin maximization through adversarial training
Gavin Weiguang Ding, Yash Sharma, Kry Yik Chau Lui, and Ruitong Huang · 2018
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Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2018
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Squeeze-and-excitation networks
Jie Hu, Li Shen, and Gang Sun · 2018
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Intriguing properties of adversarial training at scale
Cihang Xie and Alan Yuille · 2019
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Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Francesco Croce and Matthias Hein · 2020
Cited alongside, same era.
Robustbench: a standardized adversarial robustness benchmark
Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, and Matthias Hein · 2020
Cited alongside, same era.
Adversarial distributional training for robust deep learning
Yinpeng Dong, Zhijie Deng, Tianyu Pang, Jun Zhu, and Hang Su · 2020
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Advrush: Searching for adversarially robust neural architectures
Jisoo Mok, Byunggook Na, Hyeokjun Choe, and Sungroh Yoon · 2021
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Robustart: Benchmarking robustness on architecture design and training techniques
Shiyu Tang, Ruihao Gong, Yan Wang, Aishan Liu, Jiakai Wang, Xinyun Chen, Fengwei Yu, Xianglong Liu, Dawn Song, Alan Yuille, et al · 2021
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On the convergence and robustness of adversarial training
Yisen Wang, Xingjun Ma, James Bailey, Jinfeng Yi, Bowen Zhou, and Quanquan Gu · 2021
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Early convolutions help transformers see better
Tete Xiao, Mannat Singh, Eric Mintun, Trevor Darrell, Piotr Dollár, and Ross Girshick · 2021
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Parameterizing activation functions for adversarial robustness
Sihui Dai, Saeed Mahloujifar, and Prateek Mittal · 2022
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Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
Cited alongside, same era.
When nas meets robustness: In search of robust architectures against adversarial attacks
Minghao Guo, Yuzhe Yang, Rui Xu, Ziwei Liu, and Dahua Lin · 2020
Cited alongside, same era.
Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, and Piotr Dollár · 2020
Cited alongside, same era.
Do adversarially robust imagenet models transfer better?
Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, and Aleksander Madry · 2020
Cited alongside, same era.
Improving adversarial robustness requires revisiting misclassified examples
Yisen Wang, Difan Zou, Jinfeng Yi, James Bailey, Xingjun Ma, and Quanquan Gu · 2020
Cited alongside, same era.
Fast is better than free: Revisiting adversarial training
Eric Wong, Leslie Rice, and J Zico Kolter · 2020
Cited alongside, same era.
Adversarial weight perturbation helps robust generalization
Dongxian Wu, Shu-Tao Xia, and Yisen Wang · 2020
Cited alongside, same era.
A light recipe to train robust vision transformers
Edoardo Debenedetti, Vikash Sehwag, and Prateek Mittal · 2022
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Revisiting residual networks for adversarial robustness: An architectural perspective
Shihua Huang, Zhichao Lu, Kalyanmoy Deb, and Vishnu Naresh Boddeti · 2022
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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A convnet for the 2020s
Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, and Saining Xie · 2022
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When adversarial training meets vision transformers: Recipes from training to architecture
Yichuan Mo, Dongxian Wu, Yifei Wang, Yiwen Guo, and Yisen Wang · 2022
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Diffusion models for adversarial purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, and Anima Anandkumar · 2022
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Neural architecture design and robustness: A dataset
Steffen Jung, Jovita Lukasik, and Margret Keuper · 2023
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Robarch: Designing robust architectures against adversarial attacks
ShengYun Peng, Weilin Xu, Cory Cornelius, Kevin Li, Rahul Duggal, Duen Horng Chau, and Jason Martin · 2023
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Naman D Singh, Francesco Croce, and Matthias Hein · 2023
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Better diffusion models further improve adversarial training
Zekai Wang, Tianyu Pang, Chao Du, Min Lin, Weiwei Liu, and Shuicheng Yan · 2023
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Convnext v2: Co-designing and scaling convnets with masked autoencoders
Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, and Saining Xie · 2023
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