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 576–600 of 1746 papers

Title	Date	Tasks	Status
Adversarial Robustness of VAEs across Intersectional Subgroups	Jul 4, 2024	Adversarial RobustnessDimensionality Reduction	CodeCode Available
TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer Trackers	Jul 4, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available
L_p-norm Distortion-Efficient Adversarial Attack	Jul 3, 2024	Adversarial AttackAdversarial Defense	—Unverified
Learning Robust 3D Representation from CLIP via Dual Denoising	Jul 1, 2024	Adversarial RobustnessDenoising	CodeCode Available
Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness	Jun 28, 2024	Adversarial Robustness	—Unverified
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness	Jun 25, 2024	Adversarial Robustness	CodeCode Available
Diffusion-based Adversarial Purification for Intrusion Detection	Jun 25, 2024	Adversarial PurificationAdversarial Robustness	CodeCode Available
Towards unlocking the mystery of adversarial fragility of neural networks	Jun 23, 2024	Adversarial RobustnessClassification	—Unverified
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors	Jun 21, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
DataFreeShield: Defending Adversarial Attacks without Training Data	Jun 21, 2024	Adversarial RobustnessDataset Generation	—Unverified
Understanding the Robustness of Graph Neural Networks against Adversarial Attacks	Jun 20, 2024	Adversarial Robustness	CodeCode Available
Exploring Layerwise Adversarial Robustness Through the Lens of t-SNE	Jun 20, 2024	Adversarial Robustness	—Unverified
Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness	Jun 17, 2024	Adversarial RobustnessInductive Bias	CodeCode Available
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness	Jun 17, 2024	Adversarial Robustness	—Unverified
KGPA: Robustness Evaluation for Large Language Models via Cross-Domain Knowledge Graphs	Jun 16, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available
Improving Adversarial Robustness via Decoupled Visual Representation Masking	Jun 16, 2024	Adversarial DefenseAdversarial Robustness	CodeCode Available
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis	Jun 14, 2024	Adversarial Robustness	—Unverified
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences	Jun 14, 2024	Adversarial Robustnessimage-classification	CodeCode Available
Robust Information Retrieval	Jun 13, 2024	Adversarial RobustnessInformation Retrieval	—Unverified
Improving Adversarial Robustness via Feature Pattern Consistency Constraint	Jun 13, 2024	Adversarial Robustnessfeature selection	—Unverified
Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness	Jun 10, 2024	Adversarial RobustnessNeural Architecture Search	—Unverified
Large Language Model Assisted Adversarial Robustness Neural Architecture Search	Jun 8, 2024	Adversarial RobustnessCombinatorial Optimization	CodeCode Available
Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers	Jun 3, 2024	Adversarial RobustnessObject	CodeCode Available
Enhancing Adversarial Robustness in SNNs with Sparse Gradients	May 30, 2024	Adversarial Robustness	—Unverified
Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI	May 29, 2024	Adversarial Robustness	—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