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 626–650 of 1746 papers

Title	Date	Tasks	Status
Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective	Apr 30, 2024	Adversarial DefenseAdversarial Robustness	CodeCode Available
PAODING: A High-fidelity Data-free Pruning Toolkit for Debloating Pre-trained Neural Networks	Apr 30, 2024	Adversarial Robustness	—Unverified
Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks	Apr 27, 2024	Adversarial RobustnessGraph Representation Learning	CodeCode Available
Towards Robust Recommendation: A Review and an Adversarial Robustness Evaluation Library	Apr 27, 2024	Adversarial RobustnessNon-Adversarial Robustness	CodeCode Available
Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks	Apr 27, 2024	Adversarial RobustnessPrediction	—Unverified
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models	Apr 24, 2024	Adversarial RobustnessQuantum Machine Learning	—Unverified
Adversarial Robustness of Deep Learning-Based Malware Detectors via (De)Randomized Smoothing	Apr 22, 2024	Adversarial Robustness	CodeCode Available
Fermi-Bose Machine achieves both generalization and adversarial robustness	Apr 21, 2024	Adversarial RobustnessContrastive Learning	—Unverified
GenFighter: A Generative and Evolutive Textual Attack Removal	Apr 17, 2024	Adversarial RobustnessTransfer Learning	—Unverified
SpamDam: Towards Privacy-Preserving and Adversary-Resistant SMS Spam Detection	Apr 15, 2024	Adversarial RobustnessBackdoor Attack	CodeCode Available
A Survey of Neural Network Robustness Assessment in Image Recognition	Apr 12, 2024	Adversarial Robustnessimage-classification	—Unverified
Struggle with Adversarial Defense? Try Diffusion	Apr 12, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers	Apr 11, 2024	Adversarial RobustnessKnowledge Distillation	—Unverified
Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data	Apr 10, 2024	Adversarial RobustnessFederated Learning	—Unverified
On adversarial training and the 1 Nearest Neighbor classifier	Apr 9, 2024	Adversarial Robustnessimage-classification	CodeCode Available
Out-of-Distribution Data: An Acquaintance of Adversarial Examples -- A Survey	Apr 8, 2024	Adversarial RobustnessAnomaly Detection	—Unverified
Investigating the Impact of Quantization on Adversarial Robustness	Apr 8, 2024	Adversarial RobustnessQuantization	—Unverified
Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism	Apr 5, 2024	Adversarial Robustnessimage-classification	—Unverified
DiffuseMix: Label-Preserving Data Augmentation with Diffusion Models	Apr 5, 2024	Adversarial RobustnessData Augmentation	—Unverified
On Extending the Automatic Test Markup Language (ATML) for Machine Learning	Apr 4, 2024	Adversarial RobustnessDrift Detection	—Unverified
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks	Apr 4, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
On Inherent Adversarial Robustness of Active Vision Systems	Mar 29, 2024	Adversarial RobustnessFoveation	—Unverified
Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning	Mar 27, 2024	Adversarial Robustness	—Unverified
Scalable Lipschitz Estimation for CNNs	Mar 27, 2024	Adversarial Robustness	—Unverified
Boosting Adversarial Training via Fisher-Rao Norm-based Regularization	Mar 26, 2024	Adversarial Robustness	CodeCode Available

Show:10 25 50

← PrevPage 26 of 70Next →

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