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 51–75 of 1746 papers

Title	Date	Tasks	Status	Hype
Fast and Low-Cost Genomic Foundation Models via Outlier Removal	May 1, 2025	Adversarial AttackAdversarial Robustness	CodeCode Available	1
OET: Optimization-based prompt injection Evaluation Toolkit	May 1, 2025	Adversarial RobustnessNatural Language Understanding	CodeCode Available	1
Towards Robust LLMs: an Adversarial Robustness Measurement Framework	Apr 24, 2025	Adversarial RobustnessComputational Efficiency	CodeCode Available	0
Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends	Apr 21, 2025	Adversarial RobustnessDecision Making	—Unverified	0
Fast Adversarial Training with Weak-to-Strong Spatial-Temporal Consistency in the Frequency Domain on Videos	Apr 21, 2025	Adversarial RobustnessVideo Recognition	—Unverified	0
aiXamine: Simplified LLM Safety and Security	Apr 21, 2025	2kAdversarial Robustness	—Unverified	0
Hydra: An Agentic Reasoning Approach for Enhancing Adversarial Robustness and Mitigating Hallucinations in Vision-Language Models	Apr 19, 2025	Adversarial AttackAdversarial Defense	—Unverified	0
RDI: An adversarial robustness evaluation metric for deep neural networks based on model statistical features	Apr 16, 2025	Adversarial RobustnessComputational Efficiency	CodeCode Available	0
The Sword of Damocles in ViTs: Computational Redundancy Amplifies Adversarial Transferability	Apr 15, 2025	Adversarial Robustness	—Unverified	0
How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?	Apr 15, 2025	Adversarial RobustnessContrastive Learning	—Unverified	0
R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning	Apr 15, 2025	Adversarial Robustness	CodeCode Available	1
Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks	Apr 14, 2025	Adversarial RobustnessBinary Classification	—Unverified	0
Adversarial Examples in Environment Perception for Automated Driving (Review)	Apr 11, 2025	Adversarial Robustness	—Unverified	0
Toward Spiking Neural Network Local Learning Modules Resistant to Adversarial Attacks	Apr 11, 2025	Adversarial AttackAdversarial Robustness	—Unverified	0
Benchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-Judge	Apr 10, 2025	Adversarial RobustnessBenchmarking	CodeCode Available	0
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models	Apr 7, 2025	Adversarial RobustnessDiversity	—Unverified	0
A Domain-Based Taxonomy of Jailbreak Vulnerabilities in Large Language Models	Apr 7, 2025	Adversarial Robustness	—Unverified	0
Secure Diagnostics: Adversarial Robustness Meets Clinical Interpretability	Apr 7, 2025	Adversarial AttackAdversarial Robustness	—Unverified	0
A Study on Adversarial Robustness of Discriminative Prototypical Learning	Apr 3, 2025	Adversarial Robustness	CodeCode Available	0
Bridging the Theoretical Gap in Randomized Smoothing	Apr 3, 2025	Adversarial Robustness	CodeCode Available	0
AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization	Apr 2, 2025	Adversarial DefenseAdversarial Robustness	—Unverified	0
Robust Unsupervised Domain Adaptation for 3D Point Cloud Segmentation Under Source Adversarial Attacks	Apr 2, 2025	Adversarial RobustnessDecoder	—Unverified	0
ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks	Mar 26, 2025	Adversarial RobustnessComputational Efficiency	—Unverified	0
Lipschitz Constant Meets Condition Number: Learning Robust and Compact Deep Neural Networks	Mar 26, 2025	Adversarial RobustnessNetwork Pruning	—Unverified	0
Feature Statistics with Uncertainty Help Adversarial Robustness	Mar 26, 2025	Adversarial Robustness	CodeCode Available	0

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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