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 1126–1150 of 1746 papers

Title	Date	Tasks	Status
Evaluating the Adversarial Robustness for Fourier Neural Operators	Apr 8, 2022	Adversarial Robustnessscientific discovery	—Unverified
Hear No Evil: Towards Adversarial Robustness of Automatic Speech Recognition via Multi-Task Learning	Apr 5, 2022	Adversarial AttackAdversarial Robustness	—Unverified
Adversarial Robustness through the Lens of Convolutional Filters	Apr 5, 2022	Adversarial Robustness	CodeCode Available
SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning	Apr 2, 2022	Adversarial RobustnessAutonomous Driving	CodeCode Available
Scalable Whitebox Attacks on Tree-based Models	Mar 31, 2022	Adversarial Robustness	—Unverified
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes	Mar 22, 2022	Adversarial Robustness	—Unverified
Robustness through Cognitive Dissociation Mitigation in Contrastive Adversarial Training	Mar 16, 2022	Adversarial RobustnessClassification	CodeCode Available
Provable Adversarial Robustness for Fractional Lp Threat Models	Mar 16, 2022	Adversarial Robustness	CodeCode Available
Generalized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness	Mar 15, 2022	Adversarial RobustnessData Augmentation	—Unverified
Defending From Physically-Realizable Adversarial Attacks Through Internal Over-Activation Analysis	Mar 14, 2022	Adversarial Robustnessobject-detection	—Unverified
On the benefits of knowledge distillation for adversarial robustness	Mar 14, 2022	Adversarial RobustnessKnowledge Distillation	—Unverified
Perception Over Time: Temporal Dynamics for Robust Image Understanding	Mar 11, 2022	Adversarial Robustness	—Unverified
Hybrid Deep Learning Model using SPCAGAN Augmentation for Insider Threat Analysis	Mar 6, 2022	Adversarial RobustnessAnomaly Detection	—Unverified
Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers	Mar 2, 2022	Adversarial RobustnessAdversarial Text	CodeCode Available
Neuro-Symbolic Verification of Deep Neural Networks	Mar 2, 2022	Adversarial RobustnessFairness	CodeCode Available
Global-Local Regularization Via Distributional Robustness	Mar 1, 2022	Adversarial RobustnessDomain Adaptation	CodeCode Available
Adversarial robustness of sparse local Lipschitz predictors	Feb 26, 2022	Adversarial Robustness	—Unverified
Understanding Adversarial Robustness from Feature Maps of Convolutional Layers	Feb 25, 2022	Adversarial Robustness	CodeCode Available
Improving Robustness of Convolutional Neural Networks Using Element-Wise Activation Scaling	Feb 24, 2022	Adversarial Robustness	CodeCode Available
Transferring Adversarial Robustness Through Robust Representation Matching	Feb 21, 2022	Adversarial Robustness	CodeCode Available
Semi-Implicit Hybrid Gradient Methods with Application to Adversarial Robustness	Feb 21, 2022	Adversarial Robustness	—Unverified
Exploring Adversarially Robust Training for Unsupervised Domain Adaptation	Feb 18, 2022	Adversarial DefenseAdversarial Robustness	CodeCode Available
Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition	Feb 17, 2022	Adversarial RobustnessAutomatic Speech Recognition	—Unverified
Unreasonable Effectiveness of Last Hidden Layer Activations for Adversarial Robustness	Feb 15, 2022	Adversarial Robustness	—Unverified
StratDef: Strategic Defense Against Adversarial Attacks in ML-based Malware Detection	Feb 15, 2022	Adversarial RobustnessMalware Detection	—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