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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 / 3,550 papers shown
Title
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
212
0
0
28 Feb 2025
Adversarial Robustness in Parameter-Space Classifiers
Adversarial Robustness in Parameter-Space Classifiers
Tamir Shor
Ethan Fetaya
Chaim Baskin
A. Bronstein
AAML
OOD
249
0
0
27 Feb 2025
HALO: Robust Out-of-Distribution Detection via Joint Optimisation
HALO: Robust Out-of-Distribution Detection via Joint Optimisation
Hugo Lyons Keenan
S. Erfani
Christopher Leckie
OODD
214
0
0
27 Feb 2025
Stability Analysis of Deep Reinforcement Learning for Multi-Agent Inspection in a Terrestrial Testbed
Henry Lei
Zachary S. Lippay
Anonto Zaman
Joshua Aurand
Amin Maghareh
S. Phillips
42
2
0
26 Feb 2025
Steganography Beyond Space-Time with Chain of Multimodal AI
Steganography Beyond Space-Time with Chain of Multimodal AI
Ching-Chun Chang
Isao Echizen
74
0
0
25 Feb 2025
Examining the Threat Landscape: Foundation Models and Model Stealing
Examining the Threat Landscape: Foundation Models and Model Stealing
Ankita Raj
Deepankar Varma
Chetan Arora
AAML
78
1
0
25 Feb 2025
Compute Or Load KV Cache? Why Not Both?
Compute Or Load KV Cache? Why Not Both?
Shuowei Jin
Xueshen Liu
Qingzhao Zhang
Z. Morley Mao
41
7
0
24 Feb 2025
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
Wenyuan Wu
Zheng Liu
Yong Chen
Chao Su
Dezhong Peng
Xu Wang
AAML
43
0
0
24 Feb 2025
Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images
Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images
Yubo Wang
Jianting Tang
Chaohu Liu
Linli Xu
AAML
65
1
0
23 Feb 2025
Nearshore Underwater Target Detection Meets UAV-borne Hyperspectral Remote Sensing: A Novel Hybrid-level Contrastive Learning Framework and Benchmark Dataset
Nearshore Underwater Target Detection Meets UAV-borne Hyperspectral Remote Sensing: A Novel Hybrid-level Contrastive Learning Framework and Benchmark Dataset
Jiahao Qi
Chuanhong Zhou
Xingyue Liu
Chen Chen
Dehui Zhu
Kangcheng Bin
Ping Zhong
74
0
0
21 Feb 2025
Tight Clusters Make Specialized Experts
Tight Clusters Make Specialized Experts
Stefan K. Nielsen
R. Teo
Laziz U. Abdullaev
Tan M. Nguyen
MoE
66
2
0
21 Feb 2025
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness
Emanuele Ballarin
A. Ansuini
Luca Bortolussi
AAML
70
0
0
20 Feb 2025
A Transfer Attack to Image Watermarks
A Transfer Attack to Image Watermarks
Yuepeng Hu
Zhengyuan Jiang
Moyang Guo
Neil Zhenqiang Gong
77
10
0
20 Feb 2025
Shield Synthesis for LTL Modulo Theories
Shield Synthesis for LTL Modulo Theories
Andoni Rodríguez
Guy Amir
Davide Corsi
César Sánchez
Guy Katz
82
6
0
17 Feb 2025
Adversary-Aware DPO: Enhancing Safety Alignment in Vision Language Models via Adversarial Training
Adversary-Aware DPO: Enhancing Safety Alignment in Vision Language Models via Adversarial Training
Fenghua Weng
Jian Lou
Jun Feng
Minlie Huang
Wenjie Wang
AAML
75
2
0
17 Feb 2025
PAR-AdvGAN: Improving Adversarial Attack Capability with Progressive Auto-Regression AdvGAN
PAR-AdvGAN: Improving Adversarial Attack Capability with Progressive Auto-Regression AdvGAN
Jiayu Zhang
Zhiyu Zhu
Xinyi Wang
Silin Liao
Zhibo Jin
Flora Salim
Huaming Chen
GAN
52
0
0
16 Feb 2025
Jailbreaking to Jailbreak
Jailbreaking to Jailbreak
Jeremy Kritz
Vaughn Robinson
Robert Vacareanu
Bijan Varjavand
Michael Choi
Bobby Gogov
Scale Red Team
Summer Yue
Willow Primack
Zifan Wang
252
2
0
09 Feb 2025
Noise is an Efficient Learner for Zero-Shot Vision-Language Models
Raza Imam
Asif Hanif
Jian Zhang
Khaled Waleed Dawoud
Yova Kementchedjhieva
Mohammad Yaqub
VLM
58
0
0
09 Feb 2025
Secure Visual Data Processing via Federated Learning
Secure Visual Data Processing via Federated Learning
Pedro Santos
Tânia Carvalho
Filipe Magalhães
Luís Antunes
FedML
64
0
0
09 Feb 2025
Democratic Training Against Universal Adversarial Perturbations
Bing-Jie Sun
Jun Sun
Wei Zhao
AAML
68
0
0
08 Feb 2025
Confidence Elicitation: A New Attack Vector for Large Language Models
Confidence Elicitation: A New Attack Vector for Large Language Models
Brian Formento
Chuan-Sheng Foo
See-Kiong Ng
AAML
101
0
0
07 Feb 2025
How vulnerable is my policy? Adversarial attacks on modern behavior cloning policies
How vulnerable is my policy? Adversarial attacks on modern behavior cloning policies
Basavasagar Patil
Akansha Kalra
Guanhong Tao
Daniel S. Brown
AAML
76
0
0
06 Feb 2025
Adversarial ML Problems Are Getting Harder to Solve and to Evaluate
Adversarial ML Problems Are Getting Harder to Solve and to Evaluate
Javier Rando
Jie Zhang
Nicholas Carlini
F. Tramèr
AAML
ELM
68
3
0
04 Feb 2025
Dual-Flow: Transferable Multi-Target, Instance-Agnostic Attacks via In-the-wild Cascading Flow Optimization
Dual-Flow: Transferable Multi-Target, Instance-Agnostic Attacks via In-the-wild Cascading Flow Optimization
Yixiao Chen
Shikun Sun
Jianshu Li
Ruoyu Li
Zhe Li
Junliang Xing
AAML
109
0
0
04 Feb 2025
Achievable distributional robustness when the robust risk is only partially identified
Achievable distributional robustness when the robust risk is only partially identified
Julia Kostin
Nicola Gnecco
Fanny Yang
76
3
0
04 Feb 2025
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models
Amy Rafferty
Rishi Ramaesh
Ajitha Rajan
MedIm
AAML
61
0
0
04 Feb 2025
"I am bad": Interpreting Stealthy, Universal and Robust Audio Jailbreaks in Audio-Language Models
"I am bad": Interpreting Stealthy, Universal and Robust Audio Jailbreaks in Audio-Language Models
Isha Gupta
David Khachaturov
Robert D. Mullins
AAML
AuLLM
69
2
0
02 Feb 2025
Imitation Game for Adversarial Disillusion with Multimodal Generative Chain-of-Thought Role-Play
Imitation Game for Adversarial Disillusion with Multimodal Generative Chain-of-Thought Role-Play
Ching-Chun Chang
Fan-Yun Chen
Shih-Hong Gu
Kai Gao
Hanrui Wang
Isao Echizen
AAML
246
0
0
31 Jan 2025
Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks
Rorry Brenner
Laurent Itti
42
0
0
29 Jan 2025
Topological Signatures of Adversaries in Multimodal Alignments
Topological Signatures of Adversaries in Multimodal Alignments
Minh Vu
Geigh Zollicoffer
Huy Mai
B. Nebgen
Boian S. Alexandrov
Manish Bhattarai
AAML
65
0
0
29 Jan 2025
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search
Xuan Chen
Yuzhou Nie
Wenbo Guo
Xiangyu Zhang
115
10
0
28 Jan 2025
FIT-Print: Towards False-claim-resistant Model Ownership Verification via Targeted Fingerprint
Shuo Shao
Haozhe Zhu
Hongwei Yao
Yiming Li
Tianwei Zhang
Zhanyue Qin
Kui Ren
221
0
0
28 Jan 2025
Self-supervised Benchmark Lottery on ImageNet: Do Marginal Improvements Translate to Improvements on Similar Datasets?
Utku Ozbulak
Esla Timothy Anzaku
Solha Kang
W. D. Neve
J. Vankerschaver
54
0
0
28 Jan 2025
The Curious Case of Arbitrariness in Machine Learning
Prakhar Ganesh
Afaf Taik
G. Farnadi
66
2
0
28 Jan 2025
Smoothed Embeddings for Robust Language Models
Smoothed Embeddings for Robust Language Models
Ryo Hase
Md. Rafi Ur Rashid
Ashley Lewis
Jing Liu
T. Koike-Akino
K. Parsons
Yunhong Wang
AAML
48
0
0
27 Jan 2025
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks
Nasir Khan
Asmaa Abdallah
Abdulkadir Çelik
Ahmed M. Eltawil
Sinem Coleri
42
0
0
23 Jan 2025
Robust Representation Consistency Model via Contrastive Denoising
Robust Representation Consistency Model via Contrastive Denoising
Jiachen Lei
Julius Berner
Jiongxiao Wang
Zhongzhu Chen
Zhongjia Ba
Kui Ren
Jun Zhu
Anima Anandkumar
DiffM
87
0
0
22 Jan 2025
Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning
Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning
Mingyuan Fan
Zhanyi Hu
Fuyi Wang
Cen Chen
SILM
49
0
0
22 Jan 2025
Topology of Out-of-Distribution Examples in Deep Neural Networks
Topology of Out-of-Distribution Examples in Deep Neural Networks
Esha Datta
Johanna Hennig
Eva Domschot
Connor Mattes
Michael R. Smith
72
0
0
21 Jan 2025
With Great Backbones Comes Great Adversarial Transferability
With Great Backbones Comes Great Adversarial Transferability
Erik Arakelyan
Karen Hambardzumyan
Davit Papikyan
Pasquale Minervini
Albert Gordo
Isabelle Augenstein
Aram H. Markosyan
AAML
72
0
0
21 Jan 2025
On the Adversarial Vulnerabilities of Transfer Learning in Remote Sensing
On the Adversarial Vulnerabilities of Transfer Learning in Remote Sensing
Tao Bai
Xingjian Tian
Yonghao Xu
Bihan Wen
AAML
43
0
0
20 Jan 2025
Geometric Median (GM) Matching for Robust Data Pruning
Geometric Median (GM) Matching for Robust Data Pruning
Anish Acharya
Inderjit S Dhillon
Sujay Sanghavi
AAML
59
0
0
20 Jan 2025
Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach
Provably Safeguarding a Classifier from OOD and Adversarial Samples: an Extreme Value Theory Approach
Nicolas Atienza
Christophe Labreuche
Johanne Cohen
Michele Sebag
OODD
AAML
223
0
0
20 Jan 2025
Can AI-Generated Text be Reliably Detected?
Can AI-Generated Text be Reliably Detected?
Vinu Sankar Sadasivan
Aounon Kumar
S. Balasubramanian
Wenxiao Wang
S. Feizi
DeLMO
81
368
0
20 Jan 2025
Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity
Can Safety Fine-Tuning Be More Principled? Lessons Learned from Cybersecurity
David Williams-King
Linh Le
Adam Oberman
Yoshua Bengio
AAML
61
0
0
19 Jan 2025
On the uncertainty principle of neural networks
On the uncertainty principle of neural networks
Jun-Jie Zhang
Dong-xiao Zhang
Jian-Nan Chen
L. Pang
Deyu Meng
59
2
0
17 Jan 2025
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
Ping Guo
Cheng Gong
Xi Lin
Fei Liu
Zhichao Lu
Qingfu Zhang
Zhenkun Wang
AAML
48
0
0
13 Jan 2025
Protego: Detecting Adversarial Examples for Vision Transformers via Intrinsic Capabilities
Protego: Detecting Adversarial Examples for Vision Transformers via Intrinsic Capabilities
Jialin Wu
Kaikai Pan
Yanjiao Chen
Jiangyi Deng
Shengyuan Pang
Wenyuan Xu
ViT
AAML
48
0
0
13 Jan 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations
Sanghyun Hong
Fan Wu
A. Gruber
Kookjin Lee
47
0
0
12 Jan 2025
Challenging reaction prediction models to generalize to novel chemistry
Challenging reaction prediction models to generalize to novel chemistry
John Bradshaw
Anji Zhang
Babak Mahjour
David E. Graff
Marwin H. S. Segler
Connor W. Coley
47
1
0
11 Jan 2025
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