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 426–450 of 1746 papers

Title	Date	Tasks	Status	Hype
Enhance DNN Adversarial Robustness and Efficiency via Injecting Noise to Non-Essential Neurons	Feb 6, 2024	Adversarial RobustnessDecision Making	—Unverified	0
Partially Recentralization Softmax Loss for Vision-Language Models Robustness	Feb 6, 2024	Adversarial RobustnessDiversity	—Unverified	0
Exploring Biologically Inspired Mechanisms of Adversarial Robustness	Feb 5, 2024	Adversarial Robustness	—Unverified	0
Causal Feature Selection for Responsible Machine Learning	Feb 5, 2024	Adversarial RobustnessDomain Generalization	—Unverified	0
Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error	Feb 3, 2024	Adversarial RobustnessDeep Reinforcement Learning	CodeCode Available	1
MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers	Feb 3, 2024	Adversarial RobustnessRobust classification	CodeCode Available	0
σ-zero: Gradient-based Optimization of _0-norm Adversarial Examples	Feb 2, 2024	Adversarial Robustness	CodeCode Available	1
Delving into Decision-based Black-box Attacks on Semantic Segmentation	Feb 2, 2024	Adversarial RobustnessSegmentation	—Unverified	0
Achieving More Human Brain-Like Vision via Human EEG Representational Alignment	Jan 30, 2024	Adversarial RobustnessEEG	—Unverified	0
GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling	Jan 29, 2024	Adversarial RobustnessContrastive Learning	—Unverified	0
Mitigating the Impact of Noisy Edges on Graph-Based Algorithms via Adversarial Robustness Evaluation	Jan 28, 2024	Adversarial AttackAdversarial Robustness	—Unverified	0
AFD: Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement	Jan 26, 2024	Adversarial RobustnessDisentanglement	CodeCode Available	0
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective	Jan 26, 2024	Adversarial RobustnessContrastive Learning	—Unverified	0
A Training Rate and Survival Heuristic for Inference and Robustness Evaluation (TRASHFIRE)	Jan 24, 2024	Adversarial Robustness	CodeCode Available	0
Fast Adversarial Training against Textual Adversarial Attacks	Jan 23, 2024	Adversarial DefenseAdversarial Robustness	—Unverified	0
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications	Jan 20, 2024	Adversarial Robustness	—Unverified	0
The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness	Jan 19, 2024	Adversarial Robustness	—Unverified	0
Adversarial Robustness of Link Sign Prediction in Signed Graphs	Jan 19, 2024	Adversarial RobustnessContrastive Learning	—Unverified	0
Adapters Mixup: Mixing Parameter-Efficient Adapters to Enhance the Adversarial Robustness of Fine-tuned Pre-trained Text Classifiers	Jan 18, 2024	Adversarial Robustnessparameter-efficient fine-tuning	—Unverified	0
Universally Robust Graph Neural Networks by Preserving Neighbor Similarity	Jan 18, 2024	Adversarial Robustness	—Unverified	0
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images	Jan 16, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Authorship Obfuscation in Multilingual Machine-Generated Text Detection	Jan 15, 2024	Adversarial RobustnessBenchmarking	CodeCode Available	2
Robustness Against Adversarial Attacks via Learning Confined Adversarial Polytopes	Jan 15, 2024	Adversarial Robustness	—Unverified	0
Adversarial Examples are Misaligned in Diffusion Model Manifolds	Jan 12, 2024	Adversarial RobustnessImage Inpainting	—Unverified	0
Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness	Jan 9, 2024	Adversarial RobustnessZero-shot Generalization	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