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 476–500 of 1746 papers

Title	Date	Tasks	Status
A Survey and Evaluation of Adversarial Attacks for Object Detection	Aug 4, 2024	Adversarial RobustnessAutonomous Vehicles	—Unverified
Conflict-Aware Adversarial Training	Oct 21, 2024	Adversarial Robustness	—Unverified
Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI	May 29, 2024	Adversarial Robustness	—Unverified
Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training	Nov 5, 2024	Adversarial RobustnessDiversity	—Unverified
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness	Feb 11, 2022	Adversarial Robustness	—Unverified
aiXamine: Simplified LLM Safety and Security	Apr 21, 2025	2kAdversarial Robustness	—Unverified
Enhance DNN Adversarial Robustness and Efficiency via Injecting Noise to Non-Essential Neurons	Feb 6, 2024	Adversarial RobustnessDecision Making	—Unverified
SOAR: Second-Order Adversarial Regularization	Apr 4, 2020	Adversarial Robustness	—Unverified
Constrained Learning with Non-Convex Losses	Mar 8, 2021	Adversarial RobustnessFairness	—Unverified
Constraining Logits by Bounded Function for Adversarial Robustness	Oct 6, 2020	Adversarial Robustness	—Unverified
Contextual Fusion For Adversarial Robustness	Nov 18, 2020	Adversarial Robustness	—Unverified
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization	Oct 11, 2022	Adversarial DefenseAdversarial Robustness	—Unverified
Adversarially Robust Estimate and Risk Analysis in Linear Regression	Dec 18, 2020	Adversarial Robustnessregression	—Unverified
Boosting Adversarial Robustness and Generalization with Structural Prior	Feb 2, 2025	Adversarial RobustnessDeep Learning	—Unverified
Cross Domain Generative Augmentation: Domain Generalization with Latent Diffusion Models	Dec 8, 2023	Adversarial RobustnessData Augmentation	—Unverified
Cross-Entropy Loss Functions: Theoretical Analysis and Applications	Apr 14, 2023	Adversarial Robustness	—Unverified
CSTAR: Towards Compact and STructured Deep Neural Networks with Adversarial Robustness	Dec 4, 2022	Adversarial RobustnessModel Compression	—Unverified
Curvature Dynamic Black-box Attack: revisiting adversarial robustness via dynamic curvature estimation	May 25, 2025	Adversarial AttackAdversarial Robustness	—Unverified
A More Biologically Plausible Local Learning Rule for ANNs	Nov 24, 2020	Adversarial RobustnessBinary Classification	—Unverified
DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation	Feb 16, 2024	Adversarial RobustnessDomain Adaptation	—Unverified
Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness	Jun 28, 2024	Adversarial Robustness	—Unverified
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation	Jan 1, 2023	Adversarial RobustnessKnowledge Distillation	—Unverified
Adversarial Robustness Across Representation Spaces	Dec 1, 2020	Adversarial Robustnessimage-classification	—Unverified
Adversarial Robustness through Local Linearization	Jul 4, 2019	Adversarial DefenseAdversarial Robustness	—Unverified
Adversarial Robustness through Dynamic Ensemble Learning	Dec 20, 2024	Adversarial AttackAdversarial Robustness	—Unverified

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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