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Explaining and Harnessing Adversarial Examples

Explaining and Harnessing Adversarial Examples

20 December 2014
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
    AAML
    GAN
ArXivPDFHTML

Papers citing "Explaining and Harnessing Adversarial Examples"

50 / 3,605 papers shown
Title
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos
Songping Wang
Hanqing Liu
Yueming Lyu
Xiantao Hu
Ziwen He
Wenjie Wang
Caifeng Shan
Lei Wang
AAML
166
0
0
21 Apr 2025
aiXamine: Simplified LLM Safety and Security
aiXamine: Simplified LLM Safety and Security
Fatih Deniz
Dorde Popovic
Yazan Boshmaf
Euisuh Jeong
M. Ahmad
Sanjay Chawla
Issa M. Khalil
ELM
80
0
0
21 Apr 2025
Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks
Unifying Image Counterfactuals and Feature Attributions with Latent-Space Adversarial Attacks
Jeremy Goldwasser
Giles Hooker
AAML
36
0
0
21 Apr 2025
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Yi Yu
Song Xia
Xun Lin
Chenqi Kong
Wenhan Yang
Shijian Lu
Yap-Peng Tan
Alex C. Kot
AAML
SILM
223
0
0
20 Apr 2025
Rethinking Target Label Conditioning in Adversarial Attacks: A 2D Tensor-Guided Generative Approach
Rethinking Target Label Conditioning in Adversarial Attacks: A 2D Tensor-Guided Generative Approach
Hangyu Liu
Bo Peng
Pengxiang Ding
Donglin Wang
AAML
28
0
0
19 Apr 2025
Hadamard product in deep learning: Introduction, Advances and Challenges
Hadamard product in deep learning: Introduction, Advances and Challenges
Grigorios G. Chrysos
Yongtao Wu
Razvan Pascanu
Philip Torr
V. Cevher
AAML
98
1
0
17 Apr 2025
DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks
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
44
0
0
17 Apr 2025
RDI: An adversarial robustness evaluation metric for deep neural networks based on sample clustering features
RDI: An adversarial robustness evaluation metric for deep neural networks based on sample clustering features
Jialei Song
Xingquan Zuo
Feiyang Wang
Hai Huang
Tianle Zhang
AAML
169
0
0
16 Apr 2025
Human Aligned Compression for Robust Models
Human Aligned Compression for Robust Models
Samuel Räber
Andreas Plesner
Till Aczél
Roger Wattenhofer
AAML
42
0
0
16 Apr 2025
Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
Jiani Liu
Zhiyuan Wang
Zeliang Zhang
Chao Huang
Susan Liang
Yunlong Tang
Chenliang Xu
AAML
39
0
0
15 Apr 2025
Alleviating the Fear of Losing Alignment in LLM Fine-tuning
Alleviating the Fear of Losing Alignment in LLM Fine-tuning
Kang Yang
Guanhong Tao
X. Chen
Jun Xu
40
0
0
13 Apr 2025
D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition
D-Feat Occlusions: Diffusion Features for Robustness to Partial Visual Occlusions in Object Recognition
Rupayan Mallick
Sibo Dong
Nataniel Ruiz
Sarah Adel Bargal
DiffM
54
0
0
08 Apr 2025
On the Robustness of GUI Grounding Models Against Image Attacks
On the Robustness of GUI Grounding Models Against Image Attacks
Haoren Zhao
Tianyi Chen
Zhen Wang
AAML
44
2
0
07 Apr 2025
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models
Yoojin Jung
Byung Cheol Song
AAML
VLM
MQ
41
0
0
07 Apr 2025
Don't Lag, RAG: Training-Free Adversarial Detection Using RAG
Don't Lag, RAG: Training-Free Adversarial Detection Using RAG
Roie Kazoom
Raz Lapid
Moshe Sipper
Ofer Hadar
VLM
ObjD
AAML
71
0
0
07 Apr 2025
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
WeiDetect: Weibull Distribution-Based Defense against Poisoning Attacks in Federated Learning for Network Intrusion Detection Systems
S. Mandelli
Vinod Puthuvath
Anderson Rocha
Rafidha Rehiman K. A.
Mauro Conti
AAML
38
0
0
06 Apr 2025
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Sijia Zhou
Yunwen Lei
Ata Kabán
34
0
0
03 Apr 2025
Towards Assessing Deep Learning Test Input Generators
Towards Assessing Deep Learning Test Input Generators
Seif Mzoughi
Ahmed Hajyahmed
Mohamed Elshafei
Foutse Khomh anb Diego Elias Costa
D. Costa
AAML
40
0
0
03 Apr 2025
Safeguarding Vision-Language Models: Mitigating Vulnerabilities to Gaussian Noise in Perturbation-based Attacks
Safeguarding Vision-Language Models: Mitigating Vulnerabilities to Gaussian Noise in Perturbation-based Attacks
Jiawei Wang
Yushen Zuo
Yuanjun Chai
Zichen Liu
Yichen Fu
Yichun Feng
Kin-Man Lam
AAML
VLM
49
0
0
02 Apr 2025
Geometric Median Matching for Robust k-Subset Selection from Noisy Data
Geometric Median Matching for Robust k-Subset Selection from Noisy Data
Anish Acharya
Sujay Sanghavi
Alexandros G. Dimakis
Inderjit S Dhillon
AAML
62
0
0
01 Apr 2025
Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
Mahjabin Nahar
Eun-Ju Lee
Jin Won Park
Dongwon Lee
HILM
75
0
0
01 Apr 2025
Deep Neural Nets as Hamiltonians
Deep Neural Nets as Hamiltonians
Mike Winer
Boris Hanin
208
0
0
31 Mar 2025
Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios
Towards Benchmarking and Assessing the Safety and Robustness of Autonomous Driving on Safety-critical Scenarios
Jingzheng Li
Xianglong Liu
Shikui Wei
Zhijun Chen
Yangqiu Song
Qing Guo
Xianqi Yang
Yanjun Pu
Jiakai Wang
AAML
ELM
74
0
0
31 Mar 2025
A Survey on Unlearnable Data
A Survey on Unlearnable Data
Jiahao Li
Yiqiang Chen
Yunbing Xing
Yang Gu
Xiangyuan Lan
AAML
58
0
0
30 Mar 2025
Revisiting the Relationship between Adversarial and Clean Training: Why Clean Training Can Make Adversarial Training Better
Revisiting the Relationship between Adversarial and Clean Training: Why Clean Training Can Make Adversarial Training Better
MingWei Zhou
Xiaobing Pei
AAML
230
0
0
30 Mar 2025
Nested Stochastic Gradient Descent for (Generalized) Sinkhorn Distance-Regularized Distributionally Robust Optimization
Nested Stochastic Gradient Descent for (Generalized) Sinkhorn Distance-Regularized Distributionally Robust Optimization
Yue Yang
Yi Zhou
Zhaosong Lu
49
0
0
29 Mar 2025
Hi-ALPS -- An Experimental Robustness Quantification of Six LiDAR-based Object Detection Systems for Autonomous Driving
Hi-ALPS -- An Experimental Robustness Quantification of Six LiDAR-based Object Detection Systems for Autonomous Driving
Alexandra Arzberger
Ramin Tavakoli Kolagari
AAML
234
0
0
21 Mar 2025
MetaSel: A Test Selection Approach for Fine-tuned DNN Models
MetaSel: A Test Selection Approach for Fine-tuned DNN Models
Amin Abbasishahkoo
Mahboubeh Dadkhah
Lionel C. Briand
Dayi Lin
49
0
0
21 Mar 2025
SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition
SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition
Zeqi Zheng
Yanchen Huang
Yingchao Yu
Zizheng Zhu
Junfeng Tang
Zhaofei Yu
Yaochu Jin
44
0
0
20 Mar 2025
TarPro: Targeted Protection against Malicious Image Editing
TarPro: Targeted Protection against Malicious Image Editing
Kaixin Shen
Ruijie Quan
Jiaxu Miao
Jun Xiao
Yi Yang
62
1
0
18 Mar 2025
GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack
GSBAK^KK: toptoptop-KKK Geometric Score-based Black-box Attack
Md. Farhamdur Reza
Richeng Jin
Tianfu Wu
H. Dai
AAML
47
0
0
17 Mar 2025
Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization
Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization
Yuyao Zhang
Yingzhe Xu
Junyu Shi
L. Zhang
Shengshan Hu
Minghui Li
Yanjun Zhang
AAML
56
1
0
17 Mar 2025
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data
Lilin Zhang
Chengpei Wu
Ning Yang
39
0
0
14 Mar 2025
Do computer vision foundation models learn the low-level characteristics of the human visual system?
Do computer vision foundation models learn the low-level characteristics of the human visual system?
Yancheng Cai
Fei Yin
Dounia Hammou
Rafal Mantiuk
VLM
Presented at ResearchTrend Connect | VLM on 14 Mar 2025
147
1
0
13 Mar 2025
Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain
Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain
Yuanmin Huang
Mi Zhang
Zhaoxiang Wang
Wenxuan Li
Min Yang
AAML
AI4TS
61
0
0
12 Mar 2025
AdvAD: Exploring Non-Parametric Diffusion for Imperceptible Adversarial Attacks
Jin Li
Ziqiang He
Anwei Luo
Jian-Fang Hu
Zhong Wang
Xiangui Kang
DiffM
69
0
0
12 Mar 2025
Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations
Kathleen Anderson
Thomas Martinetz
CVBM
73
0
0
12 Mar 2025
MIGA: Mutual Information-Guided Attack on Denoising Models for Semantic Manipulation
Guanghao Li
Mingzhi Chen
Hao Yu
Shuting Dong
Wenhao Jiang
Ming Tang
Chun Yuan
DiffM
AAML
51
0
0
10 Mar 2025
Breaking the Limits of Quantization-Aware Defenses: QADT-R for Robustness Against Patch-Based Adversarial Attacks in QNNs
Amira Guesmi
B. Ouni
Muhammad Shafique
MQ
AAML
36
0
0
10 Mar 2025
Long-tailed Adversarial Training with Self-Distillation
Seungju Cho
Hongsin Lee
Changick Kim
AAML
TTA
265
0
0
09 Mar 2025
Exploring Adversarial Transferability between Kolmogorov-arnold Networks
Exploring Adversarial Transferability between Kolmogorov-arnold Networks
Songping Wang
Xinquan Yue
Yueming Lyu
Caifeng Shan
AAML
76
1
0
08 Mar 2025
Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models
Using Mechanistic Interpretability to Craft Adversarial Attacks against Large Language Models
Thomas Winninger
Boussad Addad
Katarzyna Kapusta
AAML
68
0
0
08 Mar 2025
Generalizable Image Repair for Robust Visual Autonomous Racing
Carson Sobolewski
Zhenjiang Mao
Kshitij Vejre
Ivan Ruchkin
57
0
0
07 Mar 2025
Scale-Invariant Adversarial Attack against Arbitrary-scale Super-resolution
Yihao Huang
Xin Luo
Yihao Huang
Felix Juefei-Xu
Xiaojun Jia
Weikai Miao
G. Pu
Yang Liu
64
1
0
06 Mar 2025
Predicting Practically? Domain Generalization for Predictive Analytics in Real-world Environments
Hanyu Duan
Yi Yang
Ahmed Abbasi
Kar Yan Tam
OOD
97
0
0
05 Mar 2025
Transformer Meets Twicing: Harnessing Unattended Residual Information
Laziz U. Abdullaev
Tan M. Nguyen
43
2
0
02 Mar 2025
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions
Wang YuHang
Junkang Guo
Aolei Liu
Kaihao Wang
Zaitong Wu
Zhenyu Liu
Wenfei Yin
Jian Liu
AAML
50
0
0
02 Mar 2025
AMUN: Adversarial Machine UNlearning
AMUN: Adversarial Machine UNlearning
A. Boroojeny
Hari Sundaram
Varun Chandrasekaran
MU
AAML
48
0
0
02 Mar 2025
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte
Ivaxi Sheth
Zhijing Jin
Mohammad Havaei
Bernhard Schölkopf
Mario Fritz
215
0
0
28 Feb 2025
Data-free Universal Adversarial Perturbation with Pseudo-semantic Prior
Data-free Universal Adversarial Perturbation with Pseudo-semantic Prior
Chanhui Lee
Yeonghwan Song
Jeany Son
AAML
216
0
0
28 Feb 2025
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