SOTAVerified

Adversarial Robustness

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

Papers

Showing 76100 of 1746 papers

TitleStatusHype
Stop Walking in Circles! Bailing Out Early in Projected Gradient Descent0
Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification0
When is dataset cartography ineffective? Using training dynamics does not improve robustness against Adversarial SQuAD0
Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers0
Robustness of deep learning classification to adversarial input on GPUs: asynchronous parallel accumulation is a source of vulnerability0
Narrowing Class-Wise Robustness Gaps in Adversarial Training0
On the Robustness Tradeoff in Fine-Tuning0
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models0
Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph Theory0
Survey of Adversarial Robustness in Multimodal Large Language Models0
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language ModelsCode0
Robust Dataset Distillation by Matching Adversarial Trajectories0
Robustness Tokens: Towards Adversarial Robustness of TransformersCode0
Quantitative Analysis of Deeply Quantized Tiny Neural Networks Robust to Adversarial Attacks0
FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation MethodsCode0
Life-Cycle Routing Vulnerabilities of LLM Router0
MMARD: Improving the Min-Max Optimization Process in Adversarial Robustness Distillation0
Long-tailed Adversarial Training with Self-Distillation0
Exploring Adversarial Transferability between Kolmogorov-arnold Networks0
Adversarial Robustness of Discriminative Self-Supervised Learning in Vision0
CLIP is Strong Enough to Fight Back: Test-time Counterattacks towards Zero-shot Adversarial Robustness of CLIPCode1
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed DistributionsCode1
Transformer Meets Twicing: Harnessing Unattended Residual InformationCode0
Adversarial Robustness in Parameter-Space Classifiers0
Evaluation of Hate Speech Detection Using Large Language Models and Geographical ContextualizationCode0
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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