SOTAVerified

Adversarial Robustness

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 551–600 of 1746 papers

TitleStatusHype
Classifier Guidance Enhances Diffusion-based Adversarial Purification by Preserving Predictive Information—0
Towards Adversarial Robustness via Debiased High-Confidence Logit Alignment—0
Adversarially Robust Industrial Anomaly Detection Through Diffusion Model—0
Towards Resilient and Efficient LLMs: A Comparative Study of Efficiency, Performance, and Adversarial Robustness—0
Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation—0
Label Augmentation for Neural Networks Robustness—0
A Survey and Evaluation of Adversarial Attacks for Object Detection—0
Vulnerabilities in AI-generated Image Detection: The Challenge of Adversarial Attacks—0
AI Safety in Practice: Enhancing Adversarial Robustness in Multimodal Image Captioning—0
RSC-SNN: Exploring the Trade-off Between Adversarial Robustness and Accuracy in Spiking Neural Networks via Randomized Smoothing CodingCode0
Adversarial Robustness in RGB-Skeleton Action Recognition: Leveraging Attention Modality Reweighter—0
Exploring the Adversarial Robustness of CLIP for AI-generated Image Detection—0
Adversarially Robust Decision TransformerCode0
Scaling Trends in Language Model RobustnessCode0
Towards Robust Vision Transformer via Masked Adaptive Ensemble—0
Beyond Dropout: Robust Convolutional Neural Networks Based on Local Feature Masking—0
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream TasksCode0
Variational Randomized Smoothing for Sample-Wise Adversarial Robustness—0
Relaxing Graph Transformers for Adversarial Attacks—0
Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques—0
Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays OffCode0
Deep Adversarial Defense Against Multilevel-Lp Attacks—0
How to beat a Bayesian adversary—0
Are Large Language Models Really Bias-Free? Jailbreak Prompts for Assessing Adversarial Robustness to Bias ElicitationCode0
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness—0
Adversarial Robustness of VAEs across Intersectional SubgroupsCode0
TrackPGD: Efficient Adversarial Attack using Object Binary Masks against Robust Transformer TrackersCode0
L_p-norm Distortion-Efficient Adversarial Attack—0
Learning Robust 3D Representation from CLIP via Dual DenoisingCode0
Data-Driven Lipschitz Continuity: A Cost-Effective Approach to Improve Adversarial Robustness—0
Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial RobustnessCode0
Diffusion-based Adversarial Purification for Intrusion DetectionCode0
Towards unlocking the mystery of adversarial fragility of neural networks—0
Deciphering the Definition of Adversarial Robustness for post-hoc OOD Detectors—0
DataFreeShield: Defending Adversarial Attacks without Training Data—0
Understanding the Robustness of Graph Neural Networks against Adversarial AttacksCode0
Exploring Layerwise Adversarial Robustness Through the Lens of t-SNE—0
Adversaries With Incentives: A Strategic Alternative to Adversarial RobustnessCode0
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness—0
KGPA: Robustness Evaluation for Large Language Models via Cross-Domain Knowledge GraphsCode0
Improving Adversarial Robustness via Decoupled Visual Representation MaskingCode0
Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis—0
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step DefencesCode0
Robust Information Retrieval—0
Improving Adversarial Robustness via Feature Pattern Consistency Constraint—0
Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness—0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
Reproducibility Study on Adversarial Attacks Against Robust Transformer TrackersCode0
Enhancing Adversarial Robustness in SNNs with Sparse Gradients—0
Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI—0
Show:102550
← PrevPage 12 of 35Next →
All datasetsAdvGLUECIFAR-10ImageNetImageNet-AImageNet-CStylized ImageNetCIFAR-100

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeBERTa (single model)Accuracy0.61—Unverified
2ALBERT (single model)Accuracy0.59—Unverified
3T5 (single model)Accuracy0.57—Unverified
4SMART_RoBERTa (single model)Accuracy0.54—Unverified
5FreeLB (single model)Accuracy0.5—Unverified
6RoBERTa (single model)Accuracy0.5—Unverified
7InfoBERT (single model)Accuracy0.46—Unverified
8ELECTRA (single model)Accuracy0.42—Unverified
9BERT (single model)Accuracy0.34—Unverified
10SMART_BERT (single model)Accuracy0.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed classifierAccuracy95.23—Unverified
2Stochastic-LWTA/PGD/WideResNet-34-10Accuracy92.26—Unverified
3Stochastic-LWTA/PGD/WideResNet-34-5Accuracy91.88—Unverified
4GLOT-DRAccuracy84.13—Unverified
5TRADES-ANCRA/ResNet18Accuracy81.7—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (SGD, Cosine)Accuracy77.4—Unverified
2ResNet-50 (SGD, Step)Accuracy76.9—Unverified
3DeiT-S (AdamW, Cosine)Accuracy76.8—Unverified
4ResNet-50 (AdamW, Cosine)Accuracy76.4—Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy12.2—Unverified
2ResNet-50 (SGD, Cosine)Accuracy3.3—Unverified
3ResNet-50 (SGD, Step)Accuracy3.2—Unverified
4ResNet-50 (AdamW, Cosine)Accuracy3.1—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (AdamW, Cosine)mean Corruption Error (mCE)59.3—Unverified
2ResNet-50 (SGD, Step)mean Corruption Error (mCE)57.9—Unverified
3ResNet-50 (SGD, Cosine)mean Corruption Error (mCE)56.9—Unverified
4DeiT-S (AdamW, Cosine)mean Corruption Error (mCE)48—Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy13—Unverified
2ResNet-50 (SGD, Cosine)Accuracy8.4—Unverified
3ResNet-50 (SGD, Step)Accuracy8.3—Unverified
4ResNet-50 (AdamW, Cosine)Accuracy8.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed ClassifierClean Accuracy85.21—Unverified
2ResNet18/MART-ANCRAClean Accuracy60.1—Unverified