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 676–700 of 1746 papers

Title	Date	Tasks	Status
Exploring Adversarial Robustness of LiDAR-Camera Fusion Model in Autonomous Driving	Dec 3, 2023	3D Object DetectionAdversarial Robustness	—Unverified
Generate and Verify: Semantically Meaningful Formal Analysis of Neural Network Perception Systems	Dec 16, 2020	Adversarial Robustness	—Unverified
Exploring Adversarial Transferability between Kolmogorov-arnold Networks	Mar 8, 2025	Adversarial RobustnessKolmogorov-Arnold Networks	—Unverified
Enhancing Adversarial Robustness via Uncertainty-Aware Distributional Adversarial Training	Nov 5, 2024	Adversarial RobustnessDiversity	—Unverified
ASAT: Adaptively Scaled Adversarial Training in Time Series	Aug 20, 2021	Adversarial RobustnessTime Series	—Unverified
Enhancing Adversarial Robustness of Vision Language Models via Adversarial Mixture Prompt Tuning	May 23, 2025	Adversarial Robustness	—Unverified
Exploring Layerwise Adversarial Robustness Through the Lens of t-SNE	Jun 20, 2024	Adversarial Robustness	—Unverified
Enhancing Adversarial Robustness of Deep Neural Networks Through Supervised Contrastive Learning	Dec 27, 2024	Adversarial RobustnessContrastive Learning	—Unverified
Exploring Robust Features for Improving Adversarial Robustness	Sep 9, 2023	Adversarial RobustnessDisentanglement	—Unverified
Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume	Mar 8, 2024	Adversarial RobustnessBenchmarking	—Unverified
Exploring the Adversarial Robustness of CLIP for AI-generated Image Detection	Jul 28, 2024	Adversarial Robustness	—Unverified
Adversarial Robustness in Two-Stage Learning-to-Defer: Algorithms and Guarantees	Feb 3, 2025	Adversarial Robustness	—Unverified
Exploring the Hyperparameter Landscape of Adversarial Robustness	May 9, 2019	Adversarial RobustnessHyperparameter Optimization	—Unverified
Exploring the Physical World Adversarial Robustness of Vehicle Detection	Aug 7, 2023	Adversarial AttackAdversarial Robustness	—Unverified
Exploring the Sharpened Cosine Similarity	Jul 25, 2023	Adversarial Robustnessimage-classification	—Unverified
Enhancing Adversarial Robustness in SNNs with Sparse Gradients	May 30, 2024	Adversarial Robustness	—Unverified
Adversarial Examples Are a Natural Consequence of Test Error in Noise	Jan 29, 2019	Adversarial Robustness	—Unverified
Adversarial Robustness in RGB-Skeleton Action Recognition: Leveraging Attention Modality Reweighter	Jul 29, 2024	Action RecognitionAdversarial Robustness	—Unverified
How Robust are Randomized Smoothing based Defenses to Data Poisoning?	Dec 2, 2020	Adversarial RobustnessBilevel Optimization	—Unverified
Adaptive Adversarial Training to Improve Adversarial Robustness of DNNs for Medical Image Segmentation and Detection	Jun 2, 2022	Adversarial RobustnessImage Segmentation	—Unverified
Extreme Miscalibration and the Illusion of Adversarial Robustness	Feb 27, 2024	Adversarial AttackAdversarial Robustness	—Unverified
F^2AT: Feature-Focusing Adversarial Training via Disentanglement of Natural and Perturbed Patterns	Oct 23, 2023	Adversarial RobustnessDisentanglement	—Unverified
Facial Attributes: Accuracy and Adversarial Robustness	Jan 4, 2018	Adversarial RobustnessAttribute	—Unverified
FADE: Enabling Federated Adversarial Training on Heterogeneous Resource-Constrained Edge Devices	Sep 8, 2022	Adversarial RobustnessFederated Learning	—Unverified
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness	Oct 21, 2021	Adversarial RobustnessCombinatorial Optimization	—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