Harnessing the Vulnerability of Latent Layers in Adversarially Trained
Models

Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models

13 May 2019

Harshitha Machiraju

Balaji Krishnamurthy

V. Balasubramanian

Papers citing "Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models"

17 / 17 papers shown

Title
Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities Zora Che Stephen Casper Robert Kirk Anirudh Satheesh Stewart Slocum ... Zikui Cai Bilal Chughtai Y. Gal Furong Huang Dylan Hadfield-Menell MU AAML ELM 85 3 0 03 Feb 2025
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging Rui Luo Jie Bao Zhixin Zhou Chuangyin Dang MedIm AAML 37 5 0 07 Nov 2024
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective Nils Philipp Walter Linara Adilova Jilles Vreeken Michael Kamp AAML 48 2 0 27 May 2024
Black-Box Access is Insufficient for Rigorous AI Audits Stephen Casper Carson Ezell Charlotte Siegmann Noam Kolt Taylor Lynn Curtis ... Michael Gerovitch David Bau Max Tegmark David M. Krueger Dylan Hadfield-Menell AAML 34 78 0 25 Jan 2024
A Survey of Adversarial CAPTCHAs on its History, Classification and Generation Zisheng Xu Qiao Yan Fei Yu Victor C.M. Leung AAML 21 1 0 22 Nov 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 37 49 0 18 May 2023
TextDefense: Adversarial Text Detection based on Word Importance Entropy Lujia Shen Xuhong Zhang S. Ji Yuwen Pu Chunpeng Ge Xing Yang Yanghe Feng AAML 15 8 0 12 Feb 2023
A comment on Guo et al. [arXiv:2206.11228] Ben Lonnqvist Harshitha Machiraju Michael H. Herzog AAML 22 0 0 02 Aug 2022
Robust Binary Models by Pruning Randomly-initialized Networks Chen Liu Ziqi Zhao Sabine Süsstrunk Mathieu Salzmann TPM AAML MQ 19 4 0 03 Feb 2022
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 15 13 0 14 Dec 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 35 17 0 09 Nov 2021
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 25 44 0 19 Apr 2021
Generating Out of Distribution Adversarial Attack using Latent Space Poisoning Ujjwal Upadhyay Prerana Mukherjee 36 6 0 09 Dec 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu-Lin Liu Liwei Wang Jiaya Jia OOD AAML 19 124 0 23 Nov 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 19 81 0 15 Jun 2020
D-square-B: Deep Distribution Bound for Natural-looking Adversarial Attack Qiuling Xu Guanhong Tao Xiangyu Zhang AAML 17 2 0 12 Jun 2020
Encryption Inspired Adversarial Defense for Visual Classification Maungmaung Aprilpyone Hitoshi Kiya 16 32 0 16 May 2020