Adversarial Robustness

Adversarial Robustness evaluates the vulnerabilities of machine learning models under various types of adversarial attacks.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 576–600 of 1746 papers

Title	Date	Tasks	Status	Score
Dynamic Time Warping based Adversarial Framework for Time-Series Domain	Jul 9, 2022	Adversarial RobustnessDynamic Time Warping	CodeCode Available	5
Adversarial robustness of amortized Bayesian inference	May 24, 2023	Adversarial RobustnessBayesian Inference	CodeCode Available	5
Generative Max-Mahalanobis Classifiers for Image Classification, Generation and More	Jan 1, 2021	Adversarial RobustnessClassification	CodeCode Available	5
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization	May 28, 2018	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Architectural Resilience to Foreground-and-Background Adversarial Noise	Mar 23, 2020	Adversarial Robustness	CodeCode Available	5
Gated Information Bottleneck for Generalization in Sequential Environments	Oct 12, 2021	Adversarial RobustnessOut of Distribution (OOD) Detection	CodeCode Available	5
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks	Feb 6, 2023	Adversarial RobustnessData Augmentation	CodeCode Available	5
Adversarial Robustness Guarantees for Gaussian Processes	Apr 7, 2021	Adversarial RobustnessGaussian Processes	CodeCode Available	5
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples	Sep 13, 2017	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Are Generative Classifiers More Robust to Adversarial Attacks?	Feb 19, 2018	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
Effective and Efficient Vote Attack on Capsule Networks	Feb 19, 2021	Adversarial Robustness	CodeCode Available	5
Generating Adversarial Examples with Adversarial Networks	Jan 8, 2018	Adversarial Robustness	CodeCode Available	5
Adversarial Robustness Guarantees for Random Deep Neural Networks	Apr 13, 2020	Adversarial RobustnessGaussian Processes	CodeCode Available	5
Are Labels Required for Improving Adversarial Robustness?	May 31, 2019	4kAdversarial Robustness	CodeCode Available	5
Give me a hint: Can LLMs take a hint to solve math problems?	Oct 8, 2024	Adversarial RobustnessMath	CodeCode Available	5
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models	Apr 19, 2023	Adversarial Robustness	CodeCode Available	5
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes	Mar 4, 2023	Adversarial RobustnessDiversity	CodeCode Available	5
Characterizing Data Point Vulnerability via Average-Case Robustness	Jul 26, 2023	Adversarial RobustnessMulti-class Classification	CodeCode Available	5
Adversarial Robustness for Visual Grounding of Multimodal Large Language Models	May 16, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Do Perceptually Aligned Gradients Imply Adversarial Robustness?	Jul 22, 2022	Adversarial RobustnessImage Classification	CodeCode Available	5
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks	Feb 2, 2022	Adversarial RobustnessTexture Synthesis	CodeCode Available	5
Don't Look into the Sun: Adversarial Solarization Attacks on Image Classifiers	Aug 24, 2023	Adversarial Robustnessimage-classification	CodeCode Available	5
FI-ODE: Certifiably Robust Forward Invariance in Neural ODEs	Oct 30, 2022	Adversarial Robustnesscontinuous-control	CodeCode Available	5
Feature Statistics with Uncertainty Help Adversarial Robustness	Mar 26, 2025	Adversarial Robustness	CodeCode Available	5
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection	May 30, 2022	Adversarial RobustnessAndroid Malware Detection	CodeCode Available	5

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All datasets AdvGLUE CIFAR-10 ImageNet ImageNet-A ImageNet-C Stylized ImageNet CIFAR-100

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeBERTa (single model)	Accuracy	0.61	—	Unverified
2	ALBERT (single model)	Accuracy	0.59	—	Unverified
3	T5 (single model)	Accuracy	0.57	—	Unverified
4	SMART_RoBERTa (single model)	Accuracy	0.54	—	Unverified
5	FreeLB (single model)	Accuracy	0.5	—	Unverified
6	RoBERTa (single model)	Accuracy	0.5	—	Unverified
7	InfoBERT (single model)	Accuracy	0.46	—	Unverified
8	ELECTRA (single model)	Accuracy	0.42	—	Unverified
9	BERT (single model)	Accuracy	0.34	—	Unverified
10	SMART_BERT (single model)	Accuracy	0.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mixed classifier	Accuracy	95.23	—	Unverified
2	Stochastic-LWTA/PGD/WideResNet-34-10	Accuracy	92.26	—	Unverified
3	Stochastic-LWTA/PGD/WideResNet-34-5	Accuracy	91.88	—	Unverified
4	GLOT-DR	Accuracy	84.13	—	Unverified
5	TRADES-ANCRA/ResNet18	Accuracy	81.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-50 (SGD, Cosine)	Accuracy	77.4	—	Unverified
2	ResNet-50 (SGD, Step)	Accuracy	76.9	—	Unverified
3	DeiT-S (AdamW, Cosine)	Accuracy	76.8	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	76.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeiT-S (AdamW, Cosine)	Accuracy	12.2	—	Unverified
2	ResNet-50 (SGD, Cosine)	Accuracy	3.3	—	Unverified
3	ResNet-50 (SGD, Step)	Accuracy	3.2	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	3.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-50 (AdamW, Cosine)	mean Corruption Error (mCE)	59.3	—	Unverified
2	ResNet-50 (SGD, Step)	mean Corruption Error (mCE)	57.9	—	Unverified
3	ResNet-50 (SGD, Cosine)	mean Corruption Error (mCE)	56.9	—	Unverified
4	DeiT-S (AdamW, Cosine)	mean Corruption Error (mCE)	48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeiT-S (AdamW, Cosine)	Accuracy	13	—	Unverified
2	ResNet-50 (SGD, Cosine)	Accuracy	8.4	—	Unverified
3	ResNet-50 (SGD, Step)	Accuracy	8.3	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	8.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mixed Classifier	Clean Accuracy	85.21	—	Unverified
2	ResNet18/MART-ANCRA	Clean Accuracy	60.1	—	Unverified