SOTAVerified

Adversarial Robustness

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

Papers

Showing 10511100 of 1746 papers

TitleStatusHype
A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?0
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial RobustnessCode0
Clustering Effect of Adversarial Robust Models0
Robustness between the worst and average caseCode0
Exponential Separation between Two Learning Models and Adversarial Robustness0
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach0
Towards a Unified Game-Theoretic View of Adversarial Perturbations and RobustnessCode1
On the Existence of The Adversarial Bayes Classifier0
Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions0
Adversarial Attacks on Graph Classifiers via Bayesian OptimisationCode1
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations0
Towards Stable and Robust AdderNets0
ExCon: Explanation-driven Supervised Contrastive Learning for Image ClassificationCode1
Clustering Effect of (Linearized) Adversarial Robust ModelsCode0
Provable Defense Against Clustering Attacks on 3D Point Clouds0
The Diversity Metrics of Sub-models based on SVD of Jacobians for Ensembles Adversarial Robustness0
Heterogeneous Architecture Search Approach within Adversarial Dynamic Defense Framework0
Revisiting Adversarial Robustness of Classifiers With a Reject Option0
Adversarial Examples on Segmentation Models Can be Easy to Transfer0
Flooding-X: Improving BERT's Resistance to Adversarial Attacks via Loss-Restricted Fine-Tuning0
Removing Out-of-Distribution Data Improves Adversarial Robustness0
Robust and Accurate Object Detection via Self-Knowledge DistillationCode0
Neural Population Geometry Reveals the Role of Stochasticity in Robust PerceptionCode0
Are Transformers More Robust Than CNNs?Code1
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search0
Characterizing the adversarial vulnerability of speech self-supervised learning0
Graph Robustness Benchmark: Benchmarking the Adversarial Robustness of Graph Machine LearningCode1
A Unified Game-Theoretic Interpretation of Adversarial RobustnessCode1
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language ModelsCode1
Adversarial Attacks on Graph Classification via Bayesian OptimisationCode1
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness0
HypMix: Hyperbolic Interpolative Data AugmentationCode1
How to Select One Among All ? An Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding0
When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?Code1
Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning ApproachCode0
Adversarial Robustness with Semi-Infinite Constrained Learning0
Holistic Deep LearningCode1
Towards Evaluating the Robustness of Neural Networks Learned by TransductionCode0
Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edge0
A Frequency Perspective of Adversarial Robustness0
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized NetworksCode1
Adversarial Robustness in Multi-Task Learning: Promises and IllusionsCode0
How and When Adversarial Robustness Transfers in Knowledge Distillation?0
Adversarial robustness for latent models: Revisiting the robust-standard accuracies tradeoff0
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness0
A Regularization Method to Improve Adversarial Robustness of Neural Networks for ECG Signal ClassificationCode1
Improving Robustness using Generated DataCode1
On the Sensitivity and Stability of Model Interpretations0
Adversarial Attacks on ML Defense Models CompetitionCode1
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness0
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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