SOTAVerified

Adversarial Robustness

Adversarial Robustness evaluates the vulnerabilities of machine learning models under various types of adversarial attacks.

Papers

Showing 14511500 of 1746 papers

TitleStatusHype
Pruning in the Face of AdversariesCode0
Improved Diffusion-based Generative Model with Better Adversarial RobustnessCode0
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output CodesCode0
Improved robustness to adversarial examples using Lipschitz regularization of the lossCode0
Improved techniques for deterministic l2 robustnessCode0
Adversarial Robustness Verification and Attack Synthesis in Stochastic SystemsCode0
Efficient Contrastive Explanations on DemandCode0
Improving Adversarial Robust Fairness via Anti-Bias Soft Label DistillationCode0
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial RobustnessCode0
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream TasksCode0
Effective and Efficient Vote Attack on Capsule NetworksCode0
Understanding the Impact of Adversarial Robustness on Accuracy DisparityCode0
Towards Practical Control of Singular Values of Convolutional LayersCode0
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious CorrelationsCode0
Improving Robustness with Adaptive Weight DecayCode0
Benchmarking Adversarial Robustness to Bias Elicitation in Large Language Models: Scalable Automated Assessment with LLM-as-a-JudgeCode0
Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural DynamicsCode0
SRoUDA: Meta Self-training for Robust Unsupervised Domain AdaptationCode0
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial ExamplesCode0
Dynamic Time Warping based Adversarial Framework for Time-Series DomainCode0
Quantization-aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural NetworksCode0
Verifying Properties of Tsetlin MachinesCode0
Do Perceptually Aligned Gradients Imply Adversarial Robustness?Code0
Don't Look into the Sun: Adversarial Solarization Attacks on Image ClassifiersCode0
Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative ModelsCode0
Queried Unlabeled Data Improves and Robustifies Class-Incremental LearningCode0
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit ConstraintsCode0
Improving Adversarial Robustness via Decoupled Visual Representation MaskingCode0
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware DetectionCode0
Towards Understanding Adversarial Robustness of Optical Flow NetworksCode0
Improving Adversarial Robustness via Guided Complement EntropyCode0
Improving Adversarial Robustness via Joint Classification and Multiple Explicit Detection ClassesCode0
Does language help generalization in vision models?Code0
RAID: A Dataset for Testing the Adversarial Robustness of AI-Generated Image DetectorsCode0
BEARD: Benchmarking the Adversarial Robustness for Dataset DistillationCode0
Improving Adversarial Robustness with Self-Paced Hard-Class Pair ReweightingCode0
Bayesian Inference with Certifiable Adversarial RobustnessCode0
An Empirical Study on the Relation between Network Interpretability and Adversarial RobustnessCode0
Improving Robustness by Enhancing Weak SubnetsCode0
Adversarial Ensemble Training by Jointly Learning Label Dependencies and Member ModelsCode0
Improving Document Binarization via Adversarial Noise-Texture AugmentationCode0
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial RobustnessCode0
RAMP: Boosting Adversarial Robustness Against Multiple l_p Perturbations for Universal RobustnessCode0
Disentangling Adversarial Robustness in Directions of the Data ManifoldCode0
Adversarial Robustness through the Lens of Convolutional FiltersCode0
Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural NetworksCode0
Randomized Smoothing with Masked Inference for Adversarially Robust Text ClassificationsCode0
Adversarial Robustness Study of Convolutional Neural Network for Lumbar Disk Shape Reconstruction from MR imagesCode0
Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural NetworksCode0
Batch Normalization Increases Adversarial Vulnerability and Decreases Adversarial Transferability: A Non-Robust Feature PerspectiveCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeBERTa (single model)Accuracy0.61Unverified
2ALBERT (single model)Accuracy0.59Unverified
3T5 (single model)Accuracy0.57Unverified
4SMART_RoBERTa (single model)Accuracy0.54Unverified
5FreeLB (single model)Accuracy0.5Unverified
6RoBERTa (single model)Accuracy0.5Unverified
7InfoBERT (single model)Accuracy0.46Unverified
8ELECTRA (single model)Accuracy0.42Unverified
9BERT (single model)Accuracy0.34Unverified
10SMART_BERT (single model)Accuracy0.3Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed classifierAccuracy95.23Unverified
2Stochastic-LWTA/PGD/WideResNet-34-10Accuracy92.26Unverified
3Stochastic-LWTA/PGD/WideResNet-34-5Accuracy91.88Unverified
4GLOT-DRAccuracy84.13Unverified
5TRADES-ANCRA/ResNet18Accuracy81.7Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (SGD, Cosine)Accuracy77.4Unverified
2ResNet-50 (SGD, Step)Accuracy76.9Unverified
3DeiT-S (AdamW, Cosine)Accuracy76.8Unverified
4ResNet-50 (AdamW, Cosine)Accuracy76.4Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy12.2Unverified
2ResNet-50 (SGD, Cosine)Accuracy3.3Unverified
3ResNet-50 (SGD, Step)Accuracy3.2Unverified
4ResNet-50 (AdamW, Cosine)Accuracy3.1Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (AdamW, Cosine)mean Corruption Error (mCE)59.3Unverified
2ResNet-50 (SGD, Step)mean Corruption Error (mCE)57.9Unverified
3ResNet-50 (SGD, Cosine)mean Corruption Error (mCE)56.9Unverified
4DeiT-S (AdamW, Cosine)mean Corruption Error (mCE)48Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy13Unverified
2ResNet-50 (SGD, Cosine)Accuracy8.4Unverified
3ResNet-50 (SGD, Step)Accuracy8.3Unverified
4ResNet-50 (AdamW, Cosine)Accuracy8.1Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed ClassifierClean Accuracy85.21Unverified
2ResNet18/MART-ANCRAClean Accuracy60.1Unverified