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 601–625 of 1746 papers

Title	Date	Tasks	Status
Robust Entropy Search for Safe Efficient Bayesian Optimization	May 29, 2024	Adversarial RobustnessBayesian Optimization	CodeCode Available
Multimodal Adversarial Defense for Vision-Language Models by Leveraging One-To-Many Relationships	May 29, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
Towards Unified Robustness Against Both Backdoor and Adversarial Attacks	May 28, 2024	Adversarial DefenseAdversarial Robustness	CodeCode Available
The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective	May 27, 2024	Adversarial Robustness	CodeCode Available
Spectral regularization for adversarially-robust representation learning	May 27, 2024	Adversarial RobustnessRepresentation Learning	CodeCode Available
TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability	May 27, 2024	Adversarial RobustnessKnowledge Distillation	—Unverified
Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness	May 25, 2024	Adversarial RobustnessData Augmentation	—Unverified
Evaluating and Safeguarding the Adversarial Robustness of Retrieval-Based In-Context Learning	May 24, 2024	Adversarial RobustnessIn-Context Learning	CodeCode Available
Can Implicit Bias Imply Adversarial Robustness?	May 24, 2024	Adversarial Robustness	—Unverified
Large Language Model Sentinel: LLM Agent for Adversarial Purification	May 24, 2024	Adversarial DefenseAdversarial Purification	—Unverified
Certified Robustness against Sparse Adversarial Perturbations via Data Localization	May 23, 2024	Adversarial Robustness	—Unverified
Adversarial Training via Adaptive Knowledge Amalgamation of an Ensemble of Teachers	May 22, 2024	Adversarial Robustness	—Unverified
Adaptive Batch Normalization Networks for Adversarial Robustness	May 20, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
Revisiting the Robust Generalization of Adversarial Prompt Tuning	May 18, 2024	Adversarial RobustnessPrompt Learning	—Unverified
Adversarial Robustness Guarantees for Quantum Classifiers	May 16, 2024	Adversarial RobustnessQuantum Machine Learning	—Unverified
Adversarial Robustness for Visual Grounding of Multimodal Large Language Models	May 16, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available
SpeechGuard: Exploring the Adversarial Robustness of Multimodal Large Language Models	May 14, 2024	Adversarial RobustnessInstruction Following	—Unverified
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks	May 14, 2024	Adversarial DefenseAdversarial Robustness	CodeCode Available
Distance-Restricted Explanations: Theoretical Underpinnings & Efficient Implementation	May 14, 2024	Adversarial RobustnessExplainable artificial intelligence	—Unverified
On the Adversarial Robustness of Learning-based Image Compression Against Rate-Distortion Attacks	May 13, 2024	Adversarial RobustnessImage Compression	—Unverified
Evaluating Adversarial Robustness in the Spatial Frequency Domain	May 10, 2024	Adversarial Robustness	—Unverified
Assessing Adversarial Robustness of Large Language Models: An Empirical Study	May 4, 2024	Adversarial Robustnesstext-classification	—Unverified
Impact of Architectural Modifications on Deep Learning Adversarial Robustness	May 3, 2024	Adversarial RobustnessDeep Learning	CodeCode Available
Robust Decentralized Learning with Local Updates and Gradient Tracking	May 2, 2024	Adversarial RobustnessEdge-computing	—Unverified
Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing	May 1, 2024	Adversarial RobustnessMalware Detection	—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