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 651–675 of 1746 papers

Title	Date	Tasks	Status
Evaluation Methodology for Attacks Against Confidence Thresholding Models	May 1, 2019	Adversarial RobustnessBenchmarking	—Unverified
A Robust Defense against Adversarial Attacks on Deep Learning-based Malware Detectors via (De)Randomized Smoothing	Feb 23, 2024	Adversarial Robustness	—Unverified
Evolutionary Reinforcement Learning: A Systematic Review and Future Directions	Feb 20, 2024	Adversarial RobustnessEvolutionary Algorithms	—Unverified
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness	Jul 7, 2023	Adversarial Robustness	—Unverified
ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks	Mar 26, 2025	Adversarial RobustnessComputational Efficiency	—Unverified
Frequency Regularization for Improving Adversarial Robustness	Dec 24, 2022	Adversarial Robustness	—Unverified
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification	Jun 18, 2022	Adversarial RobustnessBinary Classification	—Unverified
ATRAS: Adversarially Trained Robust Architecture Search	Jun 13, 2021	Adversarial Robustness	—Unverified
Experimental robustness benchmark of quantum neural network on a superconducting quantum processor	May 22, 2025	Adversarial AttackAdversarial Robustness	—Unverified
From Sound Representation to Model Robustness	Jul 27, 2020	Adversarial AttackAdversarial Robustness	—Unverified
Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training	Nov 5, 2024	Adversarial RobustnessDiversity	—Unverified
Attacking Graph Classification via Bayesian Optimisation	Jun 18, 2021	Adversarial RobustnessBayesian Optimisation	—Unverified
Adversarial Robustness of Deep Reinforcement Learning based Dynamic Recommender Systems	Dec 2, 2021	Adversarial Robustnesscounterfactual	—Unverified
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness	Sep 28, 2023	Adversarial Robustness	—Unverified
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness	Sep 15, 2022	Adversarial Robustness	—Unverified
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness	Mar 25, 2019	Adversarial Robustness	—Unverified
Exploiting Explainability to Design Adversarial Attacks and Evaluate Attack Resilience in Hate-Speech Detection Models	May 29, 2023	Adversarial RobustnessDecision Making	—Unverified
Exploiting the Relationship Between Kendall's Rank Correlation and Cosine Similarity for Attribution Protection	May 15, 2022	Adversarial Robustness	—Unverified
ASAT: Adaptively Scaled Adversarial Training in Time Series	Aug 20, 2021	Adversarial RobustnessTime Series	—Unverified
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring	Feb 13, 2024	Adversarial RobustnessDecision Making	—Unverified
Audit and Improve Robustness of Private Neural Networks on Encrypted Data	Sep 20, 2022	Adversarial RobustnessPrivacy Preserving	—Unverified
Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers	Apr 11, 2024	Adversarial RobustnessKnowledge Distillation	—Unverified
Enhancing Adversarial Robustness of Vision Language Models via Adversarial Mixture Prompt Tuning	May 23, 2025	Adversarial Robustness	—Unverified
Enhancing Adversarial Robustness of Deep Neural Networks Through Supervised Contrastive Learning	Dec 27, 2024	Adversarial RobustnessContrastive Learning	—Unverified
Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees	Feb 3, 2025	Adversarial 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