{"total":114,"rows":[{"id":"2206.10550","title":"(Certified!!) Adversarial Robustness for Free!","created":"2022-06-21","cited_by_count":132,"area":"diffusion"},{"id":"2108.00401","title":"Advances in adversarial attacks and defenses in computer vision: A survey","created":"2021-08-01","cited_by_count":127,"area":null},{"id":"2102.08452","title":"Globally-Robust Neural Networks","created":"2021-02-16","cited_by_count":108,"area":null},{"id":"2210.01787","title":"Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective","created":"2022-10-04","cited_by_count":51,"area":null},{"id":"2111.09277","title":"SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness","created":"2021-11-17","cited_by_count":49,"area":null},{"id":"2106.06946","title":"Boosting Randomized Smoothing with Variance Reduced Classifiers","created":"2021-06-13","cited_by_count":47,"area":null},{"id":"2107.10873","title":"On the Certified Robustness for Ensemble Models and Beyond","created":"2021-07-22","cited_by_count":40,"area":null},{"id":"2103.10834","title":"Improved, Deterministic Smoothing for L_1 Certified Robustness","created":"2021-03-17","cited_by_count":39,"area":null},{"id":"2107.00228","title":"Scalable Certified Segmentation via Randomized Smoothing","created":"2021-07-01","cited_by_count":35,"area":null},{"id":"2211.00322","title":"DensePure: Understanding Diffusion Models towards Adversarial Robustness","created":"2022-11-01","cited_by_count":33,"area":"diffusion"},{"id":"2107.14110","title":"Enhancing Adversarial Robustness via Test-time Transformation Ensembling","created":"2021-07-29","cited_by_count":27,"area":null},{"id":"2404.19651","title":"Provably Robust Conformal Prediction with Improved Efficiency","created":"2024-04-30","cited_by_count":27,"area":null},{"id":"2403.09606","title":"Large Language Models and Causal Inference in Collaboration: A Survey","created":"2024-03-14","cited_by_count":26,"area":null},{"id":"2106.06235","title":"Knowledge Enhanced Machine Learning Pipeline against Diverse Adversarial Attacks","created":"2021-06-11","cited_by_count":24,"area":null},{"id":"2110.06850","title":"Boosting the Certified Robustness of L-infinity Distance Nets","created":"2021-10-13","cited_by_count":24,"area":null},{"id":"2205.12331","title":"Certified Robustness Against Natural Language Attacks by Causal Intervention","created":"2022-05-24","cited_by_count":24,"area":null},{"id":"2402.02316","title":"Your Diffusion Model is Secretly a Certifiably Robust Classifier","created":"2024-02-04","cited_by_count":24,"area":"diffusion"},{"id":"2107.04570","title":"ANCER: Anisotropic Certification via Sample-wise Volume Maximization","created":"2021-07-09","cited_by_count":23,"area":null},{"id":"2202.09340","title":"Learning Physics-Informed Neural Networks without Stacked Back-propagation","created":"2022-02-18","cited_by_count":23,"area":null},{"id":"2203.06414","title":"A Survey of Adversarial Defences and Robustness in NLP","created":"2022-03-12","cited_by_count":23,"area":null},{"id":"2206.07912","title":"Double Sampling Randomized Smoothing","created":"2022-06-16","cited_by_count":22,"area":null},{"id":"2210.06983","title":"Denoising Masked AutoEncoders Help Robust Classification","created":"2022-10-10","cited_by_count":21,"area":null},{"id":"2308.14333","title":"DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing","created":"2023-08-28","cited_by_count":20,"area":"diffusion"},{"id":"2109.10696","title":"CC-Cert: A Probabilistic Approach to Certify General Robustness of Neural Networks","created":"2021-09-22","cited_by_count":19,"area":null},{"id":"2405.03316","title":"Provably Unlearnable Data Examples","created":"2024-05-06","cited_by_count":18,"area":null},{"id":"2107.00996","title":"DeformRS: Certifying Input Deformations with Randomized Smoothing","created":"2021-07-02","cited_by_count":17,"area":null},{"id":"2112.00659","title":"Certified Adversarial Defenses Meet Out-of-Distribution Corruptions: Benchmarking Robustness and Simple Baselines","created":"2021-12-01","cited_by_count":17,"area":null},{"id":"2210.06077","title":"Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity","created":"2022-10-12","cited_by_count":15,"area":null},{"id":"2404.09586","title":"Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing","created":"2024-04-15","cited_by_count":15,"area":null},{"id":"2204.00487","title":"Robust and Accurate -- Compositional Architectures for Randomized Smoothing","created":"2022-04-01","cited_by_count":12,"area":null},{"id":"2112.12084","title":"Input-Specific Robustness Certification for Randomized Smoothing","created":"2021-12-21","cited_by_count":11,"area":null},{"id":"2206.11423","title":"Input-agnostic Certified Group Fairness via Gaussian Parameter Smoothing","created":"2022-06-22","cited_by_count":11,"area":null},{"id":"2309.13794","title":"Projected Randomized Smoothing for Certified Adversarial Robustness","created":"2023-09-25","cited_by_count":11,"area":null},{"id":"2204.05687","title":"3DeformRS: Certifying Spatial Deformations on Point Clouds","created":"2022-04-12","cited_by_count":10,"area":null},{"id":"2209.05055","title":"CARE: Certifiably Robust Learning with Reasoning via Variational Inference","created":"2022-09-12","cited_by_count":10,"area":null},{"id":"2211.10752","title":"Towards Robust Dataset Learning","created":"2022-11-19","cited_by_count":9,"area":null},{"id":"2212.09000","title":"Confidence-aware Training of Smoothed Classifiers for Certified Robustness","created":"2022-12-18","cited_by_count":9,"area":null},{"id":"2310.16779","title":"Multi-scale Diffusion Denoised Smoothing","created":"2023-10-25","cited_by_count":9,"area":"diffusion"},{"id":"2302.01961","title":"Asymmetric Certified Robustness via Feature-Convex Neural Networks","created":"2023-02-03","cited_by_count":8,"area":null},{"id":"2312.03979","title":"Node-aware Bi-smoothing: Certified Robustness against Graph Injection Attacks","created":"2023-12-07","cited_by_count":8,"area":null},{"id":"2210.14283","title":"Accelerating Certified Robustness Training via Knowledge Transfer","created":"2022-10-25","cited_by_count":7,"area":null},{"id":"2305.04746","title":"Understanding Noise-Augmented Training for Randomized Smoothing","created":"2023-05-08","cited_by_count":7,"area":null},{"id":"2307.11528","title":"Improving Viewpoint Robustness for Visual Recognition via Adversarial Training","created":"2023-07-21","cited_by_count":7,"area":null},{"id":"2312.08751","title":"Improve Robustness of Reinforcement Learning against Observation Perturbations via $l_\\infty$ Lipschitz Policy Networks","created":"2023-12-14","cited_by_count":7,"area":null},{"id":"2209.15042","title":"Generalizability of Adversarial Robustness Under Distribution Shifts","created":"2022-09-29","cited_by_count":6,"area":null},{"id":"2306.08656","title":"Augment then Smooth: Reconciling Differential Privacy with Certified Robustness","created":"2023-06-14","cited_by_count":6,"area":null},{"id":"2407.20099","title":"RSC-SNN: Exploring the Trade-off Between Adversarial Robustness and Accuracy in Spiking Neural Networks via Randomized Smoothing Coding","created":"2024-07-29","cited_by_count":6,"area":null},{"id":"2103.04436","title":"Insta-RS: Instance-wise Randomized Smoothing for Improved Robustness and Accuracy","created":"2021-03-07","cited_by_count":5,"area":null},{"id":"2205.13909","title":"(De-)Randomized Smoothing for Decision Stump Ensembles","created":"2022-05-27","cited_by_count":5,"area":null},{"id":"2211.02578","title":"Data Models for Dataset Drift Controls in Machine Learning With Optical Images","created":"2022-11-04","cited_by_count":5,"area":null},{"id":"2304.02693","title":"A Certified Radius-Guided Attack Framework to Image Segmentation Models","created":"2023-04-05","cited_by_count":5,"area":null},{"id":"2405.13922","title":"Towards Certification of Uncertainty Calibration under Adversarial Attacks","created":"2024-05-22","cited_by_count":5,"area":null},{"id":"2407.05213","title":"BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Records","created":"2024-07-06","cited_by_count":5,"area":"safety"},{"id":"2206.02535","title":"Certified Robustness in Federated Learning","created":"2022-06-06","cited_by_count":4,"area":null},{"id":"2206.12364","title":"On Certifying and Improving Generalization to Unseen Domains","created":"2022-06-24","cited_by_count":4,"area":null},{"id":"2302.04379","title":"Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples","created":"2023-02-09","cited_by_count":4,"area":null},{"id":"2304.10446","title":"Certified Adversarial Robustness Within Multiple Perturbation Bounds","created":"2023-04-20","cited_by_count":4,"area":null},{"id":"2309.11005","title":"It's Simplex! Disaggregating Measures to Improve Certified Robustness","created":"2023-09-20","cited_by_count":4,"area":null},{"id":"2310.02513","title":"A Recipe for Improved Certifiable Robustness","created":"2023-10-04","cited_by_count":4,"area":null},{"id":"2311.09024","title":"Fast Certification of Vision-Language Models Using Incremental Randomized Smoothing","created":"2023-11-15","cited_by_count":4,"area":"mllm"},{"id":"2407.02811","title":"SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing","created":"2024-07-03","cited_by_count":4,"area":null},{"id":"2504.21730","title":"Cert-SSBD: Certified Backdoor Defense with Sample-Specific Smoothing Noises","created":"2025-04-30","cited_by_count":4,"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":"2108.00491","title":"Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders","created":"2021-08-01","cited_by_count":3,"area":null},{"id":"2302.02092","title":"Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics","created":"2023-02-04","cited_by_count":3,"area":null},{"id":"2312.12608","title":"Rethinking Randomized Smoothing from the Perspective of Scalability","created":"2023-12-19","cited_by_count":3,"area":null},{"id":"2407.18658","title":"Adversarial Robustification via Text-to-Image Diffusion Models","created":"2024-07-26","cited_by_count":3,"area":"diffusion"},{"id":"2410.06339","title":"Filtered Randomized Smoothing: A New Defense for Robust Modulation Classification","created":"2024-10-08","cited_by_count":3,"area":null},{"id":"2412.11066","title":"Learning Robust and Privacy-Preserving Representations via Information Theory","created":"2024-12-15","cited_by_count":3,"area":null},{"id":"2104.05888","title":"Simpler Certified Radius Maximization by Propagating Covariances","created":"2021-04-13","cited_by_count":2,"area":null},{"id":"2206.01715","title":"Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis","created":"2022-06-03","cited_by_count":2,"area":null},{"id":"2210.04076","title":"Robustness of Unsupervised Representation Learning without Labels","created":"2022-10-08","cited_by_count":2,"area":null},{"id":"2211.10882","title":"Multi-head Ensemble of Smoothed Classifiers for Certified Robustness","created":"2022-11-20","cited_by_count":2,"area":null},{"id":"2405.16036","title":"Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness","created":"2024-05-25","cited_by_count":2,"area":null},{"id":"2407.00623","title":"Consistency Purification: Effective and Efficient Diffusion Purification towards Certified Robustness","created":"2024-06-30","cited_by_count":2,"area":"diffusion"},{"id":"2503.22998","title":"AuditVotes: Elevating Provable Defense for GNNs with Efficient Augmentation and Conditional Smoothing","created":"2025-03-29","cited_by_count":2,"area":null},{"id":"2509.25979","title":"Reconcile Certified Robustness and Accuracy for DNN-based Smoothed Majority Vote Classifier","created":"2025-09-30","cited_by_count":2,"area":null},{"id":"2102.05096","title":"Towards Bridging the gap between Empirical and Certified Robustness against Adversarial Examples","created":"2021-02-09","cited_by_count":1,"area":null},{"id":"2205.06154","title":"Smooth-Reduce: Leveraging Patches for Improved Certified Robustness","created":"2022-05-12","cited_by_count":1,"area":null},{"id":"2208.07464","title":"An Overview and Prospective Outlook on Robust Training and Certification of Machine Learning Models","created":"2022-08-15","cited_by_count":1,"area":null},{"id":"2210.12952","title":"Ares: A System-Oriented Wargame Framework for Adversarial ML","created":"2022-10-24","cited_by_count":1,"area":null},{"id":"2302.00209","title":"Towards Large Certified Radius in Randomized Smoothing using Quasiconcave Optimization","created":"2023-02-01","cited_by_count":1,"area":null},{"id":"2312.09020","title":"Exploring Transferability for Randomized Smoothing","created":"2023-12-14","cited_by_count":1,"area":null},{"id":"2402.07498","title":"Accelerated Smoothing: A Scalable Approach to Randomized Smoothing","created":"2024-02-12","cited_by_count":1,"area":null},{"id":"2404.05350","title":"Certified PEFTSmoothing: Parameter-Efficient Fine-Tuning with Randomized Smoothing","created":"2024-04-08","cited_by_count":1,"area":null},{"id":"2406.01873","title":"CR-UTP: Certified Robustness against Universal Text Perturbations on Large Language Models","created":"2024-06-04","cited_by_count":1,"area":null},{"id":"2409.02802","title":"Boosting Certified Robustness for Time Series Classification with Efficient Self-Ensemble","created":"2024-09-04","cited_by_count":1,"area":null},{"id":"2410.06895","title":"Average Certified Radius is a Poor Metric for Randomized Smoothing","created":"2024-10-09","cited_by_count":1,"area":null},{"id":"2410.20432","title":"Integrating uncertainty quantification into randomized smoothing based robustness guarantees","created":"2024-10-27","cited_by_count":1,"area":null},{"id":"2501.13094","title":"Robust Representation Consistency Model via Contrastive Denoising","created":"2025-01-22","cited_by_count":1,"area":"diffusion"},{"id":"2501.17667","title":"CAMP in the Odyssey: Provably Robust Reinforcement Learning with Certified Radius Maximization","created":"2025-01-29","cited_by_count":1,"area":"deeprl"},{"id":"2510.19977","title":"Towards Strong Certified Defense with Universal Asymmetric Randomization","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2606.01437","title":"CEAR: Certified Ensemble Adversarial Robustness in DNNs","created":"2026-05-31","cited_by_count":1,"area":null},{"id":"2101.05950","title":"Robusta: Robust AutoML for Feature Selection via Reinforcement Learning","created":"2021-01-15","cited_by_count":0,"area":null},{"id":"2112.15111","title":"Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers","created":"2021-12-30","cited_by_count":0,"area":null},{"id":"2202.04978","title":"Towards Assessing and Characterizing the Semantic Robustness of Face Recognition","created":"2022-02-10","cited_by_count":0,"area":null},{"id":"2306.15221","title":"[Re] Double Sampling Randomized Smoothing","created":"2023-06-27","cited_by_count":0,"area":null},{"id":"2310.07780","title":"Promoting Robustness of Randomized Smoothing: Two Cost-Effective Approaches","created":"2023-10-11","cited_by_count":0,"area":null},{"id":"2310.08732","title":"Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing","created":"2023-10-12","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"}],"next_cursor":"100"}