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 276–300 of 1746 papers

Title	Date	Tasks	Status	Hype	Score
HybridAugment++: Unified Frequency Spectra Perturbations for Model Robustness	Jul 21, 2023	Adversarial RobustnessData Augmentation	CodeCode Available	1	5
A Unified Game-Theoretic Interpretation of Adversarial Robustness	Nov 5, 2021	Adversarial Robustness	CodeCode Available	1	5
A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow	Mar 24, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion	Mar 29, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks	Apr 1, 2024	Adversarial RobustnessAutonomous Driving	CodeCode Available	1	5
Hold me tight! Influence of discriminative features on deep network boundaries	Feb 15, 2020	Adversarial Robustness	CodeCode Available	1	5
Holistic Deep Learning	Oct 29, 2021	Adversarial RobustnessDeep Learning	CodeCode Available	1	5
Bag of Tricks for Adversarial Training	Oct 1, 2020	Adversarial RobustnessBenchmarking	CodeCode Available	1	5
Benchmarking Adversarial Robustness on Image Classification	Jun 1, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection	Mar 12, 2020	Adversarial RobustnessNovelty Detection	CodeCode Available	1	5
How Robust is Google's Bard to Adversarial Image Attacks?	Sep 21, 2023	Adversarial RobustnessChatbot	CodeCode Available	1	5
Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning	Jul 14, 2023	Adversarial Robustnessparameter estimation	CodeCode Available	1	5
Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning	Dec 31, 2020	Adversarial RobustnessData Augmentation	CodeCode Available	1	5
Adversarial Contrastive Learning via Asymmetric InfoNCE	Jul 18, 2022	Adversarial RobustnessContrastive Learning	CodeCode Available	1	5
HypMix: Hyperbolic Interpolative Data Augmentation	Nov 1, 2021	Adversarial RobustnessData Augmentation	CodeCode Available	1	5
Improve robustness of DNN for ECG signal classification:a noise-to-signal ratio perspective	May 18, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Improving Adversarial Robustness by Enforcing Local and Global Compactness	Jul 10, 2020	Adversarial RobustnessClustering	CodeCode Available	1	5
A Regularization Method to Improve Adversarial Robustness of Neural Networks for ECG Signal Classification	Oct 19, 2021	Adversarial RobustnessClassification	CodeCode Available	1	5
Improving Adversarial Robustness Requires Revisiting Misclassified Examples	May 1, 2020	Adversarial Robustness	CodeCode Available	1	5
Improving Adversarial Robustness via Mutual Information Estimation	Jul 25, 2022	Adversarial DefenseAdversarial Robustness	CodeCode Available	1	5
Certifiably Adversarially Robust Detection of Out-of-Distribution Data	Jul 16, 2020	Adversarial RobustnessOut of Distribution (OOD) Detection	CodeCode Available	1	5
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach	Oct 10, 2023	Adversarial Robustness	CodeCode Available	1	5
Are socially-aware trajectory prediction models really socially-aware?	Aug 24, 2021	Adversarial RobustnessAutonomous Navigation	CodeCode Available	1	5
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing	Jan 29, 2023	Adversarial Robustness	CodeCode Available	1	5
Towards Physically Realizable Adversarial Attacks in Embodied Vision Navigation	Sep 16, 2024	Adversarial Robustnessobject-detection	CodeCode Available	1	5

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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