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 101–125 of 1746 papers

Title	Date	Tasks	Status	Hype
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations	Jun 10, 2023	Adversarial RobustnessNovel View Synthesis	CodeCode Available	1
Multi-Objective Population Based Training	Jun 2, 2023	Adversarial RobustnessClassification	CodeCode Available	1
Red Teaming Language Model Detectors with Language Models	May 31, 2023	Adversarial RobustnessLanguage Modeling	CodeCode Available	1
Robust Classification via a Single Diffusion Model	May 24, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
Decoupled Kullback-Leibler Divergence Loss	May 23, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
Watermarking Text Generated by Black-Box Language Models	May 14, 2023	Adversarial RobustnessLanguage Modelling	CodeCode Available	1
WEDGE: A multi-weather autonomous driving dataset built from generative vision-language models	May 12, 2023	2D Object DetectionAdversarial Robustness	CodeCode Available	1
Sharpness-Aware Minimization Alone can Improve Adversarial Robustness	May 9, 2023	Adversarial RobustnessMathematical Proofs	CodeCode Available	1
Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving	Mar 30, 2023	3D Object DetectionAdversarial Robustness	CodeCode Available	1
A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion	Mar 29, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition	Mar 28, 2023	Adversarial RobustnessFace Recognition	CodeCode Available	1
CFA: Class-wise Calibrated Fair Adversarial Training	Mar 25, 2023	Adversarial RobustnessFairness	CodeCode Available	1
Feature Separation and Recalibration for Adversarial Robustness	Mar 24, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization	Mar 20, 2023	Adversarial Robustnessimage-classification	CodeCode Available	1
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness	Mar 20, 2023	Adversarial RobustnessMalware Detection	CodeCode Available	1
Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified _p Attacks	Mar 17, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression	Mar 2, 2023	Adversarial RobustnessPrediction	CodeCode Available	1
Single Image Backdoor Inversion via Robust Smoothed Classifiers	Mar 1, 2023	Adversarial RobustnessImage Generation	CodeCode Available	1
CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World	Feb 27, 2023	Adversarial Robustness	CodeCode Available	1
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness	Feb 6, 2023	Adversarial Robustness	CodeCode Available	1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks	Feb 4, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks	Jan 31, 2023	Adversarial RobustnessAutonomous Driving	CodeCode Available	1
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing	Jan 29, 2023	Adversarial Robustness	CodeCode Available	1
On the Adversarial Robustness of Camera-based 3D Object Detection	Jan 25, 2023	3D Object DetectionAdversarial Attack	CodeCode Available	1
Revisiting Residual Networks for Adversarial Robustness	Jan 1, 2023	Adversarial Robustness	CodeCode Available	1

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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