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 151–175 of 1746 papers

Title	Date	Tasks	Status	Hype	Score
Adversarial Visual Robustness by Causal Intervention	Jun 17, 2021	Adversarial Robustness	CodeCode Available	1	5
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization	Mar 5, 2020	Adversarial RobustnessData Augmentation	CodeCode Available	1	5
Adversarial vulnerability of powerful near out-of-distribution detection	Jan 18, 2022	Adversarial RobustnessOut-of-Distribution Detection	CodeCode Available	1	5
Adversarial Vulnerability of Randomized Ensembles	Jun 14, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies	Apr 14, 2024	Adversarial Robustness	CodeCode Available	1	5
AdvRush: Searching for Adversarially Robust Neural Architectures	Aug 3, 2021	Adversarial RobustnessNeural Architecture Search	CodeCode Available	1	5
Adversarial Robustness of Bottleneck Injected Deep Neural Networks for Task-Oriented Communication	Dec 13, 2024	Adversarial Robustness	CodeCode Available	1	5
Demystify Transformers & Convolutions in Modern Image Deep Networks	Nov 10, 2022	Adversarial RobustnessImage Deep Networks	CodeCode Available	1	5
Adversarial Robustness of Deep Convolutional Candlestick Learner	May 29, 2020	Adversarial Robustness	CodeCode Available	1	5
On the Adversarial Robustness of Vision Transformers	Mar 29, 2021	Adversarial Robustness	CodeCode Available	1	5
An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures	Jan 14, 2025	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
Efficient Generation of Targeted and Transferable Adversarial Examples for Vision-Language Models Via Diffusion Models	Apr 16, 2024	Adversarial DefenseAdversarial Robustness	CodeCode Available	1	5
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization	Apr 11, 2024	Adversarial Robustness	CodeCode Available	1	5
Enhancing Adversarial Robustness for Deep Metric Learning	Mar 2, 2022	Adversarial RobustnessMetric Learning	CodeCode Available	1	5
Enhancing adversarial robustness in Natural Language Inference using explanations	Sep 11, 2024	Adversarial RobustnessNatural Language Inference	CodeCode Available	1	5
Ensemble everything everywhere: Multi-scale aggregation for adversarial robustness	Aug 8, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses	Feb 28, 2022	Adversarial Robustnessimage-classification	CodeCode Available	1	5
Explainability and Adversarial Robustness for RNNs	Dec 20, 2019	Adversarial RobustnessFeature Importance	CodeCode Available	1	5
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness	Mar 20, 2023	Adversarial RobustnessMalware Detection	CodeCode Available	1	5
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation	Dec 1, 2021	Adversarial RobustnessBayesian Optimisation	CodeCode Available	1	5
Adversarial Robustness Against the Union of Multiple Threat Models	Jan 1, 2020	Adversarial Robustness	CodeCode Available	1	5
An Orthogonal Classifier for Improving the Adversarial Robustness of Neural Networks	May 19, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Fast and Low-Cost Genomic Foundation Models via Outlier Removal	May 1, 2025	Adversarial AttackAdversarial Robustness	CodeCode Available	1	5
Adversarial Robustness on In- and Out-Distribution Improves Explainability	Mar 20, 2020	Adversarial Robustnessimage-classification	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