{"total":57,"rows":[{"id":"2104.04448","title":"Relating Adversarially Robust Generalization to Flat Minima","created":"2021-04-09","cited_by_count":57,"area":null},{"id":"2104.14551","title":"Ensembling with Deep Generative Views","created":"2021-04-29","cited_by_count":53,"area":null},{"id":"2104.01789","title":"Deep Learning-Based Autonomous Driving Systems: A Survey of Attacks and Defenses","created":"2021-04-05","cited_by_count":30,"area":null},{"id":"2306.12688","title":"Towards quantum enhanced adversarial robustness in machine learning","created":"2023-06-22","cited_by_count":28,"area":null},{"id":"2106.05036","title":"Towards Defending against Adversarial Examples via Attack-Invariant Features","created":"2021-06-09","cited_by_count":25,"area":null},{"id":"2204.12347","title":"Restricted Black-box Adversarial Attack Against DeepFake Face Swapping","created":"2022-04-26","cited_by_count":25,"area":null},{"id":"2110.09903","title":"Unrestricted Adversarial Attacks on ImageNet Competition","created":"2021-10-17","cited_by_count":23,"area":null},{"id":"2106.02749","title":"Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics","created":"2021-06-04","cited_by_count":19,"area":null},{"id":"2104.09197","title":"Removing Adversarial Noise in Class Activation Feature Space","created":"2021-04-19","cited_by_count":18,"area":null},{"id":"2106.03785","title":"Generative Adversarial Networks: A Survey Towards Private and Secure Applications","created":"2021-06-07","cited_by_count":15,"area":null},{"id":"2312.08890","title":"Defenses in Adversarial Machine Learning: A Survey","created":"2023-12-13","cited_by_count":14,"area":null},{"id":"2207.12203","title":"Improving Adversarial Robustness via Mutual Information Estimation","created":"2022-07-25","cited_by_count":13,"area":null},{"id":"2101.01121","title":"Local Competition and Stochasticity for Adversarial Robustness in Deep Learning","created":"2021-01-04","cited_by_count":12,"area":null},{"id":"2206.07953","title":"Analysis and Extensions of Adversarial Training for Video Classification","created":"2022-06-16","cited_by_count":11,"area":null},{"id":"2109.09901","title":"Modeling Adversarial Noise for Adversarial Training","created":"2021-09-21","cited_by_count":8,"area":null},{"id":"2204.12050","title":"Self-recoverable Adversarial Examples: A New Effective Protection Mechanism in Social Networks","created":"2022-04-26","cited_by_count":6,"area":null},{"id":"2410.03376","title":"Mitigating Adversarial Perturbations for Deep Reinforcement Learning via Vector Quantization","created":"2024-10-04","cited_by_count":6,"area":"deeprl"},{"id":"2208.06222","title":"Scale-free and Task-agnostic Attack: Generating Photo-realistic Adversarial Patterns with Patch Quilting Generator","created":"2022-08-12","cited_by_count":5,"area":null},{"id":"2303.02874","title":"Adversarial Sampling for Fairness Testing in Deep Neural Network","created":"2023-03-06","cited_by_count":5,"area":null},{"id":"2303.06302","title":"Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey","created":"2023-03-11","cited_by_count":5,"area":null},{"id":"2404.03340","title":"Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks","created":"2024-04-04","cited_by_count":5,"area":null},{"id":"2212.05387","title":"General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments","created":"2022-12-11","cited_by_count":4,"area":null},{"id":"2106.05453","title":"Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training","created":"2021-06-10","cited_by_count":3,"area":null},{"id":"2404.01828","title":"Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay","created":"2024-04-02","cited_by_count":3,"area":null},{"id":"2106.04225","title":"On the role of feedback in visual processing: a predictive coding perspective","created":"2021-06-08","cited_by_count":2,"area":null},{"id":"2312.07338","title":"Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identification","created":"2023-12-12","cited_by_count":2,"area":null},{"id":"2406.03117","title":"VQUNet: Vector Quantization U-Net for Defending Adversarial Atacks by Regularizing Unwanted Noise","created":"2024-06-05","cited_by_count":2,"area":null},{"id":"2508.17680","title":"Robustness Feature Adapter for Efficient Adversarial Training","created":"2025-08-25","cited_by_count":2,"area":null},{"id":"2102.07304","title":"CAP-GAN: Towards Adversarial Robustness with Cycle-consistent Attentional Purification","created":"2021-02-15","cited_by_count":1,"area":null},{"id":"2103.04513","title":"Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN","created":"2021-03-08","cited_by_count":1,"area":null},{"id":"2202.07342","title":"Unreasonable Effectiveness of Last Hidden Layer Activations for Adversarial Robustness","created":"2022-02-15","cited_by_count":1,"area":null},{"id":"2401.14232","title":"AR-GAN: Generative Adversarial Network-Based Defense Method Against Adversarial Attacks on the Traffic Sign Classification System of Autonomous Vehicles","created":"2023-12-31","cited_by_count":1,"area":null},{"id":"2408.00329","title":"OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack","created":"2024-08-01","cited_by_count":1,"area":null},{"id":"2509.07495","title":"Generating Transferrable Adversarial Examples via Local Mixing and Logits Optimization for Remote Sensing Object Recognition","created":"2025-09-09","cited_by_count":1,"area":null},{"id":"2510.27245","title":"Trans-defense: Transformer-based Denoiser for Adversarial Defense with Spatial-Frequency Domain Representation","created":"2025-10-31","cited_by_count":1,"area":null},{"id":"2104.01494","title":"Mitigating Gradient-based Adversarial Attacks via Denoising and Compression","created":"2021-04-03","cited_by_count":0,"area":null},{"id":"2105.06807","title":"Salient Feature Extractor for Adversarial Defense on Deep Neural Networks","created":"2021-05-14","cited_by_count":0,"area":null},{"id":"2106.04392","title":"Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition","created":"2021-06-05","cited_by_count":0,"area":null},{"id":"2106.11644","title":"NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations","created":"2021-06-22","cited_by_count":0,"area":null},{"id":"2208.11839","title":"A Perturbation Resistant Transformation and Classification System for Deep Neural Networks","created":"2022-08-25","cited_by_count":0,"area":null},{"id":"2307.05095","title":"ATWM: Defense against adversarial malware based on adversarial training","created":"2023-07-11","cited_by_count":0,"area":null},{"id":"2309.09443","title":"Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adapter","created":"2023-09-18","cited_by_count":0,"area":null},{"id":"2311.08141","title":"GMTR: Graph Matching Transformers","created":"2023-11-14","cited_by_count":0,"area":null},{"id":"2311.13841","title":"Adversarial defense based on distribution transfer","created":"2023-11-23","cited_by_count":0,"area":"diffusion"},{"id":"2312.16805","title":"DarkShot: Lighting Dark Images with Low-Compute and High-Quality","created":"2023-12-28","cited_by_count":0,"area":null},{"id":"2401.05431","title":"TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processing","created":"2024-01-06","cited_by_count":0,"area":null},{"id":"2401.05432","title":"TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks","created":"2024-01-06","cited_by_count":0,"area":null},{"id":"2403.13663","title":"T-Pixel2Mesh: Combining Global and Local Transformer for 3D Mesh Generation from a Single Image","created":"2024-03-20","cited_by_count":0,"area":null},{"id":"2408.00023","title":"On the Perturbed States for Transformed Input-robust Reinforcement Learning","created":"2024-07-31","cited_by_count":0,"area":"deeprl"},{"id":"2408.17101","title":"Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithms","created":"2024-08-30","cited_by_count":0,"area":null},{"id":"2410.11162","title":"Towards General Deepfake Detection with Dynamic Curriculum","created":"2024-10-15","cited_by_count":0,"area":null},{"id":"2410.13409","title":"Attr-Int: A Simple and Effective Entity Alignment Framework for Heterogeneous Knowledge Graphs","created":"2024-10-17","cited_by_count":0,"area":null},{"id":"2502.03758","title":"Improving Adversarial Robustness via Phase and Amplitude-aware Prompting","created":"2025-02-06","cited_by_count":0,"area":null},{"id":"2506.08255","title":"SHIELD: Secure Hypernetworks for Incremental Expansion Learning Defense","created":"2025-06-09","cited_by_count":0,"area":null},{"id":"2507.06486","title":"Mask6D: Masked Pose Priors For 6D Object Pose Estimation","created":"2025-07-09","cited_by_count":0,"area":null},{"id":"2508.19290","title":"Efficient Model-Based Purification Against Adversarial Attacks for LiDAR Segmentation","created":"2025-08-25","cited_by_count":0,"area":null},{"id":"2604.14200","title":"Retina gap junctions support the robust perception by warping neural representational geometries along the visual hierarchy","created":"2026-04-03","cited_by_count":0,"area":null}],"next_cursor":null}