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 376–400 of 1746 papers

Title	Date	Tasks	Status	Score
Adversarial Robustness via Fisher-Rao Regularization	Jun 12, 2021	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks	Feb 2, 2022	Adversarial RobustnessTexture Synthesis	CodeCode Available	5
FI-ODE: Certifiably Robust Forward Invariance in Neural ODEs	Oct 30, 2022	Adversarial Robustnesscontinuous-control	CodeCode Available	5
Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack	Jan 1, 2025	3D ReconstructionAdversarial Attack	CodeCode Available	5
Bridging the Performance Gap between FGSM and PGD Adversarial Training	Nov 7, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems	Oct 5, 2021	Adversarial Robustness	CodeCode Available	5
Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach	Jul 14, 2025	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
Bridging Adversarial Robustness and Gradient Interpretability	Mar 27, 2019	Adversarial Robustness	CodeCode Available	5
Feature Statistics with Uncertainty Help Adversarial Robustness	Mar 26, 2025	Adversarial Robustness	CodeCode Available	5
Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks	Apr 27, 2024	Adversarial RobustnessGraph Representation Learning	CodeCode Available	5
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack	Jun 15, 2022	Adversarial RobustnessComputational Efficiency	CodeCode Available	5
Adversarial Robustness through the Lens of Convolutional Filters	Apr 5, 2022	Adversarial Robustness	CodeCode Available	5
Feature Denoising for Improving Adversarial Robustness	Dec 9, 2018	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
Boosting Adversarial Training via Fisher-Rao Norm-based Regularization	Mar 26, 2024	Adversarial Robustness	CodeCode Available	5
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms	Dec 1, 2020	Adversarial RobustnessQuantization	CodeCode Available	5
Boosting Adversarial Robustness using Feature Level Stochastic Smoothing	Jun 10, 2023	Adversarial RobustnessAutonomous Navigation	CodeCode Available	5
Adversarially Robust Learning with Optimal Transport Regularized Divergences	Sep 7, 2023	Adversarial RobustnessDeep Learning	CodeCode Available	5
Fake It Until You Break It: On the Adversarial Robustness of AI-generated Image Detectors	Oct 2, 2024	Adversarial RobustnessMisinformation	CodeCode Available	5
Fast Adversarial Training with Smooth Convergence	Aug 24, 2023	Adversarial Robustness	CodeCode Available	5
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness	Aug 16, 2023	Adversarial RobustnessSubgraph Counting	CodeCode Available	5
Expressive Losses for Verified Robustness via Convex Combinations	May 23, 2023	Adversarial Robustness	CodeCode Available	5
FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods	Mar 11, 2025	Adversarial RobustnessFace Detection	CodeCode Available	5
Bridging the Gap Between Adversarial Robustness and Optimization Bias	Feb 17, 2021	Adversarial Robustness	CodeCode Available	5
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming	Jun 19, 2023	Adversarial RobustnessComputational Efficiency	CodeCode Available	5
FaiR-N: Fair and Robust Neural Networks for Structured Data	Oct 13, 2020	Adversarial RobustnessAttribute	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