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 601–625 of 1746 papers

Title	Date	Tasks	Status	Score
Gradient-Free Adversarial Attacks for Bayesian Neural Networks	Dec 23, 2020	Adversarial RobustnessBayesian Inference	CodeCode Available	5
Improved Adversarial Training Through Adaptive Instance-wise Loss Smoothing	Mar 24, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Improving Robustness of Convolutional Neural Networks Using Element-Wise Activation Scaling	Feb 24, 2022	Adversarial Robustness	CodeCode Available	5
Adversarial Robustness for Visual Grounding of Multimodal Large Language Models	May 16, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Do Perceptually Aligned Gradients Imply Adversarial Robustness?	Jul 22, 2022	Adversarial RobustnessImage Classification	CodeCode Available	5
Enhancing 3D Robotic Vision Robustness by Minimizing Adversarial Mutual Information through a Curriculum Training Approach	Sep 19, 2024	Adversarial Robustnessobject-detection	CodeCode Available	5
Don't Look into the Sun: Adversarial Solarization Attacks on Image Classifiers	Aug 24, 2023	Adversarial Robustnessimage-classification	CodeCode Available	5
GenAttack: Practical Black-box Attacks with Gradient-Free Optimization	May 28, 2018	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection	May 30, 2022	Adversarial RobustnessAndroid Malware Detection	CodeCode Available	5
Exploring the Landscape of Spatial Robustness	Dec 7, 2017	Adversarial RobustnessData Augmentation	CodeCode Available	5
Gated Information Bottleneck for Generalization in Sequential Environments	Oct 12, 2021	Adversarial RobustnessOut of Distribution (OOD) Detection	CodeCode Available	5
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes	Mar 4, 2023	Adversarial RobustnessDiversity	CodeCode Available	5
GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks	Feb 6, 2023	Adversarial RobustnessData Augmentation	CodeCode Available	5
Generating Adversarial Examples with Adversarial Networks	Jan 8, 2018	Adversarial Robustness	CodeCode Available	5
Does language help generalization in vision models?	Apr 16, 2021	Adversarial RobustnessClustering	CodeCode Available	5
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness	Dec 7, 2019	Adversarial RobustnessImage Classification	CodeCode Available	5
Enhancing Adversarial Training via Reweighting Optimization Trajectory	Jun 25, 2023	Adversarial Robustness	CodeCode Available	5
APRICOT: A Dataset of Physical Adversarial Attacks on Object Detection	Dec 17, 2019	Adversarial RobustnessDensity Estimation	CodeCode Available	5
A practical approach to evaluating the adversarial distance for machine learning classifiers	Sep 5, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics	Jun 2, 2023	Adversarial Robustness	CodeCode Available	5
Efficiently Training Low-Curvature Neural Networks	Jun 14, 2022	Adversarial Robustness	CodeCode Available	5
Approximate Manifold Defense Against Multiple Adversarial Perturbations	Apr 5, 2020	Adversarial Robustnessimage-classification	CodeCode Available	5
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks	Feb 2, 2022	Adversarial RobustnessTexture Synthesis	CodeCode Available	5
Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks	Aug 16, 2020	Adversarial Robustness	CodeCode Available	5
FI-ODE: Certifiably Robust Forward Invariance in Neural ODEs	Oct 30, 2022	Adversarial Robustnesscontinuous-control	CodeCode Available	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