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 1451–1475 of 1746 papers

Title	Date	Tasks	Status	Hype
Multitask Learning Strengthens Adversarial Robustness	Jul 14, 2020	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
Adversarial robustness via robust low rank representations	Jul 13, 2020	Adversarial Robustness	CodeCode Available	0
Understanding Object Detection Through An Adversarial Lens	Jul 11, 2020	Adversarial RobustnessAutonomous Vehicles	CodeCode Available	1
Improving Adversarial Robustness by Enforcing Local and Global Compactness	Jul 10, 2020	Adversarial RobustnessClustering	CodeCode Available	1
RobFR: Benchmarking Adversarial Robustness on Face Recognition	Jul 8, 2020	Adversarial RobustnessBenchmarking	CodeCode Available	1
How benign is benign overfitting?	Jul 8, 2020	Adversarial RobustnessRepresentation Learning	—Unverified	0
On Connections between Regularizations for Improving DNN Robustness	Jul 4, 2020	Adversarial RobustnessBIG-bench Machine Learning	—Unverified	0
Trace-Norm Adversarial Examples	Jul 2, 2020	Adversarial Robustness	—Unverified	0
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey	Jul 1, 2020	Adversarial RobustnessBIG-bench Machine Learning	—Unverified	0
Biologically Inspired Mechanisms for Adversarial Robustness	Jun 29, 2020	Adversarial Robustness	CodeCode Available	0
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification	Jun 29, 2020	Adversarial RobustnessClassification	—Unverified	0
Improving Calibration through the Relationship with Adversarial Robustness	Jun 29, 2020	Adversarial Robustness	—Unverified	0
Proper Network Interpretability Helps Adversarial Robustness in Classification	Jun 26, 2020	Adversarial RobustnessClassification	CodeCode Available	1
Smooth Adversarial Training	Jun 25, 2020	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness	Jun 24, 2020	Adversarial Robustness	CodeCode Available	1
Adversarial Robustness of Deep Sensor Fusion Models	Jun 23, 2020	2D Object DetectionAdversarial Robustness	—Unverified	0
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models	Jun 22, 2020	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
How do SGD hyperparameters in natural training affect adversarial robustness?	Jun 20, 2020	Adversarial Robustness	—Unverified	0
Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples	Jun 19, 2020	Adversarial RobustnessVocal Bursts Intensity Prediction	—Unverified	0
The Dilemma Between Data Transformations and Adversarial Robustness for Time Series Application Systems	Jun 18, 2020	Adversarial RobustnessDecision Making	—Unverified	0
Local Competition and Uncertainty for Adversarial Robustness in Deep Learning	Jun 18, 2020	Adversarial AttackAdversarial Robustness	—Unverified	0
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets	Jun 17, 2020	Adversarial RobustnessGeneral Classification	CodeCode Available	0
Classifier-independent Lower-Bounds for Adversarial Robustness	Jun 17, 2020	Adversarial AttackAdversarial Robustness	—Unverified	0
On sparse connectivity, adversarial robustness, and a novel model of the artificial neuron	Jun 16, 2020	Adversarial RobustnessComputational Efficiency	—Unverified	0
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness	Jun 16, 2020	Adversarial Robustness	—Unverified	0

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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