{"total":31,"rows":[{"id":"2204.05255","title":"Narcissus: A Practical Clean-Label Backdoor Attack with Limited Information","created":"2022-04-11","cited_by_count":103,"area":null},{"id":"2103.03344","title":"WaveGuard: Understanding and Mitigating Audio Adversarial Examples","created":"2021-03-04","cited_by_count":40,"area":null},{"id":"2301.13838","title":"Image Shortcut Squeezing: Countering Perturbative Availability Poisons with Compression","created":"2023-01-31","cited_by_count":39,"area":null},{"id":"2402.02333","title":"Copyright Protection in Generative AI: A Technical Perspective","created":"2024-02-04","cited_by_count":38,"area":null},{"id":"2209.14262","title":"A Survey on Physical Adversarial Attack in Computer Vision","created":"2022-09-28","cited_by_count":25,"area":null},{"id":"2205.09619","title":"Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification","created":"2022-05-19","cited_by_count":16,"area":null},{"id":"2206.10057","title":"Robust Deep Reinforcement Learning through Bootstrapped Opportunistic Curriculum","created":"2022-06-21","cited_by_count":15,"area":null},{"id":"2207.11378","title":"Do Perceptually Aligned Gradients Imply Adversarial Robustness?","created":"2022-07-22","cited_by_count":15,"area":null},{"id":"2207.03574","title":"Demystifying the Adversarial Robustness of Random Transformation Defenses","created":"2022-06-18","cited_by_count":14,"area":null},{"id":"2403.16271","title":"Object Detectors in the Open Environment: Challenges, Solutions, and Outlook","created":"2024-03-24","cited_by_count":13,"area":null},{"id":"2310.03578","title":"Targeted Adversarial Attacks on Generalizable Neural Radiance Fields","created":"2023-10-05","cited_by_count":10,"area":null},{"id":"2402.01239","title":"PRIME: Protect Your Videos From Malicious Editing","created":"2024-02-02","cited_by_count":9,"area":null},{"id":"2301.12993","title":"Benchmarking Robustness to Adversarial Image Obfuscations","created":"2023-01-30","cited_by_count":8,"area":null},{"id":"2404.10727","title":"How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model","created":"2024-04-16","cited_by_count":7,"area":null},{"id":"2504.10888","title":"CDUPatch: Color-Driven Universal Adversarial Patch Attack for Dual-Modal Visible-Infrared Detectors","created":"2025-04-15","cited_by_count":6,"area":null},{"id":"2306.07033","title":"When Vision Fails: Text Attacks Against ViT and OCR","created":"2023-06-12","cited_by_count":5,"area":null},{"id":"2103.15385","title":"Lagrangian Objective Function Leads to Improved Unforeseen Attack Generalization in Adversarial Training","created":"2021-03-29","cited_by_count":3,"area":null},{"id":"2107.05780","title":"Detect and Defense Against Adversarial Examples in Deep Learning using Natural Scene Statistics and Adaptive Denoising","created":"2021-07-12","cited_by_count":3,"area":null},{"id":"2202.03651","title":"Causal Scene BERT: Improving object detection by searching for challenging groups of data","created":"2022-02-08","cited_by_count":3,"area":null},{"id":"2601.21933","title":"Just Noticeable Difference Modeling for Deep Visual Features","created":"2026-01-29","cited_by_count":3,"area":null},{"id":"2307.13131","title":"Why Don't You Clean Your Glasses? Perception Attacks with Dynamic Optical Perturbations","created":"2023-07-24","cited_by_count":2,"area":null},{"id":"2506.06027","title":"Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification","created":"2025-06-06","cited_by_count":2,"area":null},{"id":"2210.08178","title":"Is Face Recognition Safe from Realizable Attacks?","created":"2022-10-15","cited_by_count":1,"area":null},{"id":"2408.06625","title":"DePatch: Towards Robust Adversarial Patch for Evading Person Detectors in the Real World","created":"2024-08-13","cited_by_count":1,"area":null},{"id":"2103.06487","title":"DAFAR: Defending against Adversaries by Feedback-Autoencoder Reconstruction","created":"2021-03-11","cited_by_count":0,"area":null},{"id":"2408.02814","title":"Pre-trained Encoder Inference: Revealing Upstream Encoders In Downstream Machine Learning Services","created":"2024-08-05","cited_by_count":0,"area":null},{"id":"2412.07253","title":"CapGen:An Environment-Adaptive Generator of Adversarial Patches","created":"2024-12-10","cited_by_count":0,"area":null},{"id":"2511.06495","title":"Probably Approximately Global Robustness Certification","created":"2025-11-09","cited_by_count":0,"area":null},{"id":"2602.19071","title":"Defining Explainable AI for Requirements Analysis","created":"2026-02-22","cited_by_count":0,"area":null},{"id":"2605.30578","title":"AdvScene: Rethinking Adversarial Patch Evaluation Through Scene Robustness","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2610.11534","title":"HAND: A Biologically-Inspired Activation Function that Improves Generalisation and Sample Efficiency in Image Classification","created":"2026-10-08","cited_by_count":0,"area":null}],"next_cursor":null}