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1902.06705
Cited By
On Evaluating Adversarial Robustness
18 February 2019
Nicholas Carlini
Anish Athalye
Nicolas Papernot
Wieland Brendel
Jonas Rauber
Dimitris Tsipras
Ian Goodfellow
A. Madry
Alexey Kurakin
ELM
AAML
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Papers citing
"On Evaluating Adversarial Robustness"
50 / 151 papers shown
Title
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Yi-Lin Sung
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Mohit Bansal
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83
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OET: Optimization-based prompt injection Evaluation Toolkit
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Chaowei Xiao
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Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments
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W. Wang
Yixiu Mao
Yiqin Lv
Xiangyang Ji
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Manipulating Multimodal Agents via Cross-Modal Prompt Injection
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Tianyuan Zhang
Siyuan Liang
Shengshan Hu
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Fatima M. Anwar
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03 Feb 2025
The Pitfalls of "Security by Obscurity" And What They Mean for Transparent AI
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Olivia Mundahl
Sunoo Park
74
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0
30 Jan 2025
The Curious Case of Arbitrariness in Machine Learning
Prakhar Ganesh
Afaf Taik
G. Farnadi
59
2
0
28 Jan 2025
CaFA: Cost-aware, Feasible Attacks With Database Constraints Against Neural Tabular Classifiers
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Daniel Deutch
Nave Frost
Mahmood Sharif
AAML
107
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0
20 Jan 2025
Challenging reaction prediction models to generalize to novel chemistry
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Anji Zhang
Babak Mahjour
David E. Graff
Marwin H. S. Segler
Connor W. Coley
40
1
0
11 Jan 2025
Towards Unbiased and Robust Spatio-Temporal Scene Graph Generation and Anticipation
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Saurabh
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The Effects of Multi-Task Learning on ReLU Neural Network Functions
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Joseph Shenouda
Robert D. Nowak
34
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29 Oct 2024
Do Unlearning Methods Remove Information from Language Model Weights?
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Fabien Roger
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MU
40
14
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11 Oct 2024
Improving Adversarial Robustness for 3D Point Cloud Recognition at Test-Time through Purified Self-Training
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Xulei Yang
Tianrui Li
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Kureha Yamaguchi
Margaux Leblanc
Simon Malzard
Varun Chhabra
Victoria Nockles
Yue-bo Wu
AAML
37
0
0
08 Sep 2024
Adversarial Robustification via Text-to-Image Diffusion Models
Daewon Choi
Jongheon Jeong
Huiwon Jang
Jinwoo Shin
DiffM
41
1
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26 Jul 2024
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors
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Mario Fernandez
Jens Müller
Ullrich Kothe
AAML
78
1
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21 Jun 2024
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure
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Ruoxi Sun
Minhui Xue
Sheng Wen
S. Çamtepe
Surya Nepal
Yang Xiang
39
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0
24 May 2024
AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
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Jérôme Rony
Maura Pintor
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Battista Biggio
Ismail Ben Ayed
Fabio Roli
ELM
AAML
SILM
44
6
0
30 Apr 2024
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks
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Tim G. J. Rudner
Nikolaos Tsilivis
Julia Kempe
AAML
BDL
43
1
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27 Apr 2024
A Survey of Neural Network Robustness Assessment in Image Recognition
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Jun Ai
Minyan Lu
Haoran Su
Dan Yu
Yutao Zhang
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Jingyu Liu
AAML
30
3
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12 Apr 2024
Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
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Francesco Croce
Nicolas Flammarion
AAML
83
159
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02 Apr 2024
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?
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Sahar Abdelnabi
Soroush Tabesh
Mario Fritz
Christoph H. Lampert
50
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11 Mar 2024
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit
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Yang He
Zhangqian Bi
Jianguo Zhang
Hongyu Zhang
Yulei Sui
Guandong Xu
Hai Jin
Philip S. Yu
30
20
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Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness
Ambar Pal
Huaijin Hao
René Vidal
26
8
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28 Sep 2023
Certified Robust Models with Slack Control and Large Lipschitz Constants
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David Stutz
Bernt Schiele
Mario Fritz
14
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12 Sep 2023
HoSNN: Adversarially-Robust Homeostatic Spiking Neural Networks with Adaptive Firing Thresholds
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Peng Li
AAML
34
3
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20 Aug 2023
Robustified ANNs Reveal Wormholes Between Human Category Percepts
Guy Gaziv
Michael J. Lee
J. DiCarlo
AAML
24
6
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14 Aug 2023
Training on Foveated Images Improves Robustness to Adversarial Attacks
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Bhiksha Raj
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30
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A LLM Assisted Exploitation of AI-Guardian
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20 Jul 2023
On building machine learning pipelines for Android malware detection: a procedural survey of practices, challenges and opportunities
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I. Abualhaol
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Yang Zhou
Ronnie Salvador Giagone
Huang Shengqiang
18
11
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12 Jun 2023
SoK: Pragmatic Assessment of Machine Learning for Network Intrusion Detection
Giovanni Apruzzese
P. Laskov
J. Schneider
36
24
0
30 Apr 2023
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking
Chang-Shu Liu
Yinpeng Dong
Wenzhao Xiang
X. Yang
Hang Su
Junyi Zhu
YueFeng Chen
Yuan He
H. Xue
Shibao Zheng
OOD
VLM
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33
72
0
28 Feb 2023
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition
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Edward Raff
Cynthia Matuszek
AAML
16
2
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17 Feb 2023
On the Efficacy of Metrics to Describe Adversarial Attacks
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T. Zoppi
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17
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Benchmarking Robustness to Adversarial Image Obfuscations
Florian Stimberg
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...
Merve Kaya
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29
10
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Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
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24
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"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice
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Fabio Pierazzi
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AAML
31
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Confidence-aware Training of Smoothed Classifiers for Certified Robustness
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AAML
21
7
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On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices
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Yves Le Traon
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Towards Good Practices in Evaluating Transfer Adversarial Attacks
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Defending with Errors: Approximate Computing for Robustness of Deep Neural Networks
Amira Guesmi
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Mohamed Abid
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22
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Multi-view Representation Learning from Malware to Defend Against Adversarial Variants
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Weifeng Li
Xin Li
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13
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25 Oct 2022
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network
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Jun Yan
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Scaling Laws for Reward Model Overoptimization
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John Schulman
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ALM
38
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On the Adversarial Robustness of Mixture of Experts
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Rodolphe Jenatton
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Srinadh Bhojanapalli
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37
18
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Scaling Adversarial Training to Large Perturbation Bounds
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30
22
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Strength-Adaptive Adversarial Training
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Dawei Zhou
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Jun Yu
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17
2
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A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks
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Mathieu Dumont
Pierre-Alain Moëllic
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19
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AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
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Chaowei Xiao
Anima Anandkumar
Danfei Xu
Marco Pavone
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30
62
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19 Sep 2022
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