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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 71–80 of 1746 papers

Title	Date	Tasks	Status	Hype
Robust Unsupervised Domain Adaptation for 3D Point Cloud Segmentation Under Source Adversarial Attacks	Apr 2, 2025	Adversarial RobustnessDecoder	—Unverified	0
AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization	Apr 2, 2025	Adversarial DefenseAdversarial Robustness	—Unverified	0
ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks	Mar 26, 2025	Adversarial RobustnessComputational Efficiency	—Unverified	0
Feature Statistics with Uncertainty Help Adversarial Robustness	Mar 26, 2025	Adversarial Robustness	CodeCode Available	0
Lipschitz Constant Meets Condition Number: Learning Robust and Compact Deep Neural Networks	Mar 26, 2025	Adversarial RobustnessNetwork Pruning	—Unverified	0
Stop Walking in Circles! Bailing Out Early in Projected Gradient Descent	Mar 25, 2025	Adversarial Robustness	—Unverified	0
Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification	Mar 24, 2025	Adversarial RobustnessAuthorship Verification	—Unverified	0
When is dataset cartography ineffective? Using training dynamics does not improve robustness against Adversarial SQuAD	Mar 24, 2025	Adversarial RobustnessExtractive Question-Answering	—Unverified	0
Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers	Mar 21, 2025	Adversarial RobustnessFairness	—Unverified	0
Robustness of deep learning classification to adversarial input on GPUs: asynchronous parallel accumulation is a source of vulnerability	Mar 21, 2025	Adversarial RobustnessBayesian Optimization	—Unverified	0

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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