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 276–300 of 1746 papers

Title	Date	Tasks	Status	Hype
RobFR: Benchmarking Adversarial Robustness on Face Recognition	Jul 8, 2020	Adversarial RobustnessBenchmarking	CodeCode Available	1
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks	Oct 26, 2021	Adversarial Robustness	CodeCode Available	1
A Perturbation-Constrained Adversarial Attack for Evaluating the Robustness of Optical Flow	Mar 24, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	1
A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion	Mar 29, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Exploring Adversarial Robustness of Deep State Space Models	Jun 8, 2024	Adversarial RobustnessState Space Models	CodeCode Available	1
Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization	Apr 11, 2024	Adversarial Robustness	CodeCode Available	1
Engineering flexible machine learning systems by traversing functionally-invariant paths	Apr 30, 2022	Adversarial RobustnessContinual Learning	CodeCode Available	1
Enhancing Adversarial Robustness via Score-Based Optimization	Jul 10, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available	1
Enhancing Adversarial Robustness via Test-time Transformation Ensembling	Jul 29, 2021	Adversarial Robustness	CodeCode Available	1
ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection	Mar 12, 2020	Adversarial RobustnessNovelty Detection	CodeCode Available	1
Ensemble everything everywhere: Multi-scale aggregation for adversarial robustness	Aug 8, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning	Mar 28, 2020	Adversarial Robustness	CodeCode Available	1
A Unified Game-Theoretic Interpretation of Adversarial Robustness	Nov 5, 2021	Adversarial Robustness	CodeCode Available	1
Adversarial Contrastive Learning via Asymmetric InfoNCE	Jul 18, 2022	Adversarial RobustnessContrastive Learning	CodeCode Available	1
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks	Oct 7, 2021	Adversarial Robustness	CodeCode Available	1
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches	Mar 7, 2022	Adversarial RobustnessBenchmarking	CodeCode Available	1
Feature Separation and Recalibration for Adversarial Robustness	Mar 24, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1
A Regularization Method to Improve Adversarial Robustness of Neural Networks for ECG Signal Classification	Oct 19, 2021	Adversarial RobustnessClassification	CodeCode Available	1
FedNest: Federated Bilevel, Minimax, and Compositional Optimization	May 4, 2022	Adversarial RobustnessHyperparameter Optimization	CodeCode Available	1
On the Adversarial Robustness of Multi-Modal Foundation Models	Aug 21, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	1
FlowPure: Continuous Normalizing Flows for Adversarial Purification	May 19, 2025	Adversarial PurificationAdversarial Robustness	CodeCode Available	1
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach	Oct 10, 2023	Adversarial Robustness	CodeCode Available	1
Are socially-aware trajectory prediction models really socially-aware?	Aug 24, 2021	Adversarial RobustnessAutonomous Navigation	CodeCode Available	1
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger	Feb 26, 2020	Adversarial Robustness	CodeCode Available	1
Towards Physically Realizable Adversarial Attacks in Embodied Vision Navigation	Sep 16, 2024	Adversarial Robustnessobject-detection	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