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
On the Adversarial Robustness of Benjamini Hochberg	Jan 6, 2025	Adversarial RobustnessAnomaly Detection	—Unverified
Adversarial Training for Face Recognition Systems using Contrastive Adversarial Learning and Triplet Loss Fine-tuning	Oct 9, 2021	Adversarial RobustnessFace Recognition	—Unverified
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction	Sep 19, 2022	Adversarial AttackAdversarial Robustness	—Unverified
Challenging the adversarial robustness of DNNs based on error-correcting output codes	Mar 26, 2020	Adversarial AttackAdversarial Robustness	—Unverified
On the Adversarial Robustness of Generative Autoencoders in the Latent Space	Jul 5, 2023	Adversarial Robustnesscompressed sensing	—Unverified
On the Adversarial Robustness of Graph Contrastive Learning Methods	Nov 29, 2023	Adversarial RobustnessContrastive Learning	—Unverified
On the Adversarial Robustness of LASSO Based Feature Selection	Oct 20, 2020	Adversarial Robustnessfeature selection	—Unverified
On the Adversarial Robustness of Learning-based Image Compression Against Rate-Distortion Attacks	May 13, 2024	Adversarial RobustnessImage Compression	—Unverified
On the Adversarial Robustness of Mixture of Experts	Oct 19, 2022	Adversarial RobustnessMixture-of-Experts	—Unverified
Adversarial Test on Learnable Image Encryption	Jul 31, 2019	Adversarial RobustnessPrivacy Preserving	—Unverified
On the Adversarial Robustness of Multivariate Robust Estimation	Mar 27, 2019	Adversarial Robustness	—Unverified
On the Adversarial Robustness of Neural Networks without Weight Transport	Aug 9, 2019	Adversarial Robustness	—Unverified
On the Adversarial Robustness of Quantized Neural Networks	May 1, 2021	Adversarial RobustnessModel Compression	—Unverified
On the Adversarial Robustness of Subspace Learning	Aug 17, 2019	Adversarial Robustness	—Unverified
On the benefits of knowledge distillation for adversarial robustness	Mar 14, 2022	Adversarial RobustnessKnowledge Distillation	—Unverified
Stochastic Security as a Performance Metric for Quantum-enhanced Generative AI	May 13, 2023	Adversarial Robustness	—Unverified
Towards A Unified Min-Max Framework for Adversarial Exploration and Robustness	Sep 25, 2019	Adversarial AttackAdversarial Robustness	—Unverified
Adversarial Robustness with Semi-Infinite Constrained Learning	Oct 29, 2021	Adversarial Robustness	—Unverified
On the Effectiveness of Low Frequency Perturbations	Feb 28, 2019	Adversarial AttackAdversarial Robustness	—Unverified
On the Effectiveness of Minimal Context Selection for Robust Question Answering	Oct 30, 2018	Adversarial RobustnessQuestion Answering	—Unverified
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks	Jan 29, 2019	Adversarial Robustness	—Unverified
On the Effect of Pruning on Adversarial Robustness	Aug 10, 2021	Adversarial Robustness	—Unverified
AI Safety in Practice: Enhancing Adversarial Robustness in Multimodal Image Captioning	Jul 30, 2024	Adversarial RobustnessComputational Efficiency	—Unverified
On the Existence of The Adversarial Bayes Classifier	Dec 1, 2021	Adversarial Robustness	—Unverified
On the Existence of the Adversarial Bayes Classifier (Extended Version)	Dec 3, 2021	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