Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better

18 August 2021

Papers citing "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"

23 / 23 papers shown

Title
DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks Jing Chen Onat Gungor Zhengli Shang Elvin Li T. Rosing AAML 47 0 0 17 Apr 2025
Revisiting the Relationship between Adversarial and Clean Training: Why Clean Training Can Make Adversarial Training Better MingWei Zhou Xiaobing Pei AAML 253 0 0 30 Mar 2025
Adversarial Prompt Distillation for Vision-Language Models Lin Luo Xin Wang Bojia Zi Shihao Zhao Xingjun Ma Yu-Gang Jiang AAML VLM 89 2 0 22 Nov 2024
Dynamic Guidance Adversarial Distillation with Enhanced Teacher Knowledge Hyejin Park Dongbo Min AAML 47 2 0 03 Sep 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 56 17 0 28 Feb 2024
Linearizing Models for Efficient yet Robust Private Inference Sreetama Sarkar Souvik Kundu Peter A. Beerel AAML 22 0 0 08 Feb 2024
Indirect Gradient Matching for Adversarial Robust Distillation Hongsin Lee Seungju Cho Changick Kim AAML FedML 53 2 0 06 Dec 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 57 51 0 18 May 2023
CAT:Collaborative Adversarial Training Xingbin Liu Huafeng Kuang Xianming Lin Yongjian Wu Rongrong Ji AAML 27 4 0 27 Mar 2023
Data-free Defense of Black Box Models Against Adversarial Attacks Gaurav Kumar Nayak Inder Khatri Ruchit Rawal Anirban Chakraborty AAML 33 1 0 03 Nov 2022
Maximum Likelihood Distillation for Robust Modulation Classification Javier Maroto Gérôme Bovet P. Frossard AAML 23 5 0 01 Nov 2022
ARDIR: Improving Robustness using Knowledge Distillation of Internal Representation Tomokatsu Takahashi Masanori Yamada Yuuki Yamanaka Tomoya Yamashita 28 0 0 01 Nov 2022
Accelerating Certified Robustness Training via Knowledge Transfer Pratik Vaishnavi Kevin Eykholt Amir Rahmati 34 7 0 25 Oct 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 54 9 0 23 May 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training Tianlong Chen Zhenyu Zhang Pengju Wang Santosh Balachandra Haoyu Ma Zehao Wang Zhangyang Wang OOD AAML 100 47 0 20 Feb 2022
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 40 15 0 30 Jan 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 215 345 0 15 Dec 2021
Iterative Teaching by Label Synthesis Weiyang Liu Zhen Liu Hanchen Wang Liam Paull Bernhard Schölkopf Adrian Weller 50 16 0 27 Oct 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 48 100 0 07 Oct 2021
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 167 224 0 08 Mar 2020
3D Point Cloud Processing and Learning for Autonomous Driving Siheng Chen Baoan Liu Chen Feng Carlos Vallespi-Gonzalez Carl K. Wellington 3DPC 61 164 0 01 Mar 2020
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 69 264 0 30 Nov 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 359 5,849 0 08 Jul 2016