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Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
Neural Information Processing Systems (NeurIPS), 2021
9 February 2021
Lue Tao
Lei Feng
Jinfeng Yi
Sheng-Jun Huang
Songcan Chen
AAML
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Papers citing
"Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training"
36 / 36 papers shown
Provable Watermarking for Data Poisoning Attacks
Yifan Zhu
Lijia Yu
Xiao-Shan Gao
AAML
166
2
0
10 Oct 2025
How Far Are We from True Unlearnability?
International Conference on Learning Representations (ICLR), 2025
Kai Ye
Liangcai Su
Chenxiong Qian
295
6
0
09 Sep 2025
Failure Cases Are Better Learned But Boundary Says Sorry: Facilitating Smooth Perception Change for Accuracy-Robustness Trade-Off in Adversarial Training
Yanyun Wang
Li Liu
AAML
210
1
0
04 Aug 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond
Qiongxiu Li
Xiaoyu Luo
Yiyi Chen
Johannes Bjerva
596
8
0
10 Mar 2025
Game-Theoretic Defenses for Robust Conformal Prediction Against Adversarial Attacks in Medical Imaging
Rui Luo
Jie Bao
Zhixin Zhou
Chuangyin Dang
MedIm
AAML
603
10
0
07 Nov 2024
Empirical Perturbation Analysis of Linear System Solvers from a Data Poisoning Perspective
Yixin Liu
Arielle Carr
Lichao Sun
AAML
247
0
0
01 Oct 2024
Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI
Robert Honig
Javier Rando
Nicholas Carlini
Florian Tramèr
WIGM
AAML
520
41
0
17 Jun 2024
Nonlinear Transformations Against Unlearnable Datasets
T. Hapuarachchi
Jing Lin
Kaiqi Xiong
Mohamed Rahouti
Gitte Ost
332
4
0
05 Jun 2024
PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
Sunay Bhat
Jeffrey Q. Jiang
Omead Brandon Pooladzandi
Alexander Branch
Gregory Pottie
AAML
434
4
0
28 May 2024
Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
International Conference on Machine Learning (ICML), 2024
Yi Yu
Yufei Wang
Song Xia
Wenhan Yang
Shijian Lu
Yap-Peng Tan
A.C. Kot
AAML
330
22
0
02 May 2024
Data-Dependent Stability Analysis of Adversarial Training
Yihan Wang
Shuang Liu
Xiao-Shan Gao
378
6
0
06 Jan 2024
A Comprehensive Survey of Attack Techniques, Implementation, and Mitigation Strategies in Large Language Models
Aysan Esmradi
Daniel Wankit Yip
C. Chan
AAML
299
29
0
18 Dec 2023
HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks
Industrial Conference on Data Mining (IDM), 2023
Minh-Hao Van
Alycia N. Carey
Xintao Wu
TDI
AAML
326
3
0
15 Sep 2023
APBench: A Unified Benchmark for Availability Poisoning Attacks and Defenses
Tianrui Qin
Xitong Gao
Juanjuan Zhao
Kejiang Ye
Chengjie Xu
AAML
267
8
0
07 Aug 2023
What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?
Neural Information Processing Systems (NeurIPS), 2023
Fnu Suya
X. Zhang
Yuan Tian
David Evans
OOD
AAML
363
3
0
03 Jul 2023
Exploring Model Dynamics for Accumulative Poisoning Discovery
International Conference on Machine Learning (ICML), 2023
Jianing Zhu
Xiawei Guo
Jiangchao Yao
Chao Du
Li He
Shuo Yuan
Tongliang Liu
Liang Wang
Bo Han
AAML
244
0
0
06 Jun 2023
Unlearnable Examples for Diffusion Models: Protect Data from Unauthorized Exploitation
Zhengyue Zhao
Jinhao Duan
Xingui Hu
Kaidi Xu
Chenan Wang
Rui Zhang
Zidong Du
Qi Guo
Yunji Chen
DiffM
WIGM
342
40
0
02 Jun 2023
What Can We Learn from Unlearnable Datasets?
Neural Information Processing Systems (NeurIPS), 2023
Pedro Sandoval-Segura
Vasu Singla
Jonas Geiping
Micah Goldblum
Tom Goldstein
330
23
0
30 May 2023
Sharpness-Aware Data Poisoning Attack
International Conference on Learning Representations (ICLR), 2023
Pengfei He
Han Xu
Jie Ren
Yingqian Cui
Hui Liu
Charu C. Aggarwal
Shucheng Zhou
AAML
518
9
0
24 May 2023
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks
Jingfeng Zhang
Bo Song
Bo Han
Lei Liu
Gang Niu
Masashi Sugiyama
AAML
205
2
0
30 Apr 2023
Learning the Unlearnable: Adversarial Augmentations Suppress Unlearnable Example Attacks
Tianrui Qin
Xitong Gao
Juanjuan Zhao
Kejiang Ye
Chengzhong Xu
AAML
MU
226
38
0
27 Mar 2023
The Devil's Advocate: Shattering the Illusion of Unexploitable Data using Diffusion Models
H. M. Dolatabadi
S. Erfani
C. Leckie
DiffM
373
22
0
15 Mar 2023
CUDA: Convolution-based Unlearnable Datasets
Computer Vision and Pattern Recognition (CVPR), 2023
Vinu Sankar Sadasivan
Mahdi Soltanolkotabi
Soheil Feizi
MU
348
33
0
07 Mar 2023
Not All Poisons are Created Equal: Robust Training against Data Poisoning
International Conference on Machine Learning (ICML), 2022
Yu Yang
Tianwei Liu
Baharan Mirzasoleiman
AAML
178
45
0
18 Oct 2022
Towards Fair Classification against Poisoning Attacks
Han Xu
Xiaorui Liu
Yuxuan Wan
Shucheng Zhou
265
4
0
18 Oct 2022
Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks
Neural Information Processing Systems (NeurIPS), 2022
Tianwei Liu
Yu Yang
Baharan Mirzasoleiman
AAML
392
39
0
14 Aug 2022
Autoregressive Perturbations for Data Poisoning
Neural Information Processing Systems (NeurIPS), 2022
Pedro Sandoval-Segura
Vasu Singla
Jonas Geiping
Micah Goldblum
Tom Goldstein
David Jacobs
AAML
502
57
0
08 Jun 2022
Robust Unlearnable Examples: Protecting Data Against Adversarial Learning
Shaopeng Fu
Fengxiang He
Yang Liu
Li Shen
Dacheng Tao
205
43
0
28 Mar 2022
Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
International Conference on Learning Representations (ICLR), 2022
Hao He
Kaiwen Zha
Dina Katabi
AAML
464
44
0
22 Feb 2022
On the Effectiveness of Adversarial Training against Backdoor Attacks
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Yinghua Gao
Dongxian Wu
Jingfeng Zhang
Guanhao Gan
Shutao Xia
Gang Niu
Masashi Sugiyama
AAML
231
33
0
22 Feb 2022
Can Adversarial Training Be Manipulated By Non-Robust Features?
Neural Information Processing Systems (NeurIPS), 2022
Lue Tao
Lei Feng
Jianguo Huang
Jinfeng Yi
Sheng-Jun Huang
Songcan Chen
AAML
768
17
0
31 Jan 2022
Fooling Adversarial Training with Inducing Noise
Zhirui Wang
Yifei Wang
Yisen Wang
167
14
0
19 Nov 2021
Adversarial Neuron Pruning Purifies Backdoored Deep Models
Dongxian Wu
Yisen Wang
AAML
392
386
0
27 Oct 2021
Trustworthy AI: A Computational Perspective
Haochen Liu
Yiqi Wang
Wenqi Fan
Xiaorui Liu
Yaxin Li
Shaili Jain
Yunhao Liu
Anil K. Jain
Shucheng Zhou
FaML
500
272
0
12 Jul 2021
What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning
Jonas Geiping
Liam H. Fowl
Gowthami Somepalli
Micah Goldblum
Michael Moeller
Tom Goldstein
TDI
AAML
SILM
239
47
0
26 Feb 2021
With False Friends Like These, Who Can Notice Mistakes?
AAAI Conference on Artificial Intelligence (AAAI), 2020
Lue Tao
Lei Feng
Jinfeng Yi
Songcan Chen
AAML
488
6
0
29 Dec 2020
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