{"total":23,"rows":[{"id":"2307.10562","title":"Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples","created":"2023-07-20","cited_by_count":43,"area":null},{"id":"2210.04886","title":"Revisiting adapters with adversarial training","created":"2022-10-10","cited_by_count":18,"area":null},{"id":"2303.13846","title":"Feature Separation and Recalibration for Adversarial Robustness","created":"2023-03-24","cited_by_count":16,"area":null},{"id":"2301.12576","title":"Uncovering Adversarial Risks of Test-Time Adaptation","created":"2023-01-29","cited_by_count":12,"area":null},{"id":"2308.06703","title":"Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods","created":"2023-08-13","cited_by_count":8,"area":null},{"id":"2309.15224","title":"Collaborative Watermarking for Adversarial Speech Synthesis","created":"2023-09-26","cited_by_count":7,"area":null},{"id":"2311.09266","title":"Adversarially Robust Spiking Neural Networks Through Conversion","created":"2023-11-15","cited_by_count":7,"area":null},{"id":"2410.15042","title":"Adversarial Training: A Survey","created":"2024-10-19","cited_by_count":6,"area":null},{"id":"2310.02480","title":"Splitting the Difference on Adversarial Training","created":"2023-10-03","cited_by_count":5,"area":null},{"id":"2407.15385","title":"Towards Robust Vision Transformer via Masked Adaptive Ensemble","created":"2024-07-22","cited_by_count":4,"area":null},{"id":"2409.13382","title":"Audio Codec Augmentation for Robust Collaborative Watermarking of Speech Synthesis","created":"2024-09-20","cited_by_count":4,"area":null},{"id":"2510.03224","title":"Test-Time Defense Against Adversarial Attacks via Stochastic Resonance of Latent Ensembles","created":"2025-10-03","cited_by_count":2,"area":null},{"id":"2410.16579","title":"Conflict-Aware Adversarial Training","created":"2024-10-21","cited_by_count":1,"area":null},{"id":"2501.08005","title":"DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection","created":"2025-01-14","cited_by_count":1,"area":null},{"id":"2605.24420","title":"Batch Normalization Amplifies Memorization and Privacy Risks","created":"2026-05-23","cited_by_count":1,"area":null},{"id":"2210.02411","title":"Dynamical Isometry for Residual Networks","created":"2022-10-05","cited_by_count":0,"area":null},{"id":"2302.08973","title":"Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition","created":"2023-02-17","cited_by_count":0,"area":null},{"id":"2303.06425","title":"Improving the Robustness of Deep Convolutional Neural Networks Through Feature Learning","created":"2023-03-11","cited_by_count":0,"area":null},{"id":"2403.16569","title":"Revealing Vulnerabilities of Neural Networks in Parameter Learning and Defense Against Explanation-Aware Backdoors","created":"2024-03-25","cited_by_count":0,"area":null},{"id":"2502.16610","title":"AdverX-Ray: Ensuring X-Ray Integrity Through Frequency-Sensitive Adversarial VAEs","created":"2025-02-23","cited_by_count":0,"area":null},{"id":"2503.16975","title":"EasyRobust: A Comprehensive and Easy-to-use Toolkit for Robust and Generalized Vision","created":"2025-03-21","cited_by_count":0,"area":null},{"id":"2509.16833","title":"SOLAR: Switchable Output Layer for Accuracy and Robustness in Once-for-All Training","created":"2025-09-20","cited_by_count":0,"area":null},{"id":"2603.25517","title":"NERO-Net: A Neuroevolutionary Approach for the Design of Adversarially Robust CNNs","created":"2026-03-26","cited_by_count":0,"area":null}],"next_cursor":null}