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Can Shape Structure Features Improve Model Robustness under Diverse Adversarial Settings?, , , , , , and . ICCV, page 7506-7515. IEEE, (2021)Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features., , , , , and . USENIX Security Symposium, page 285-302. USENIX Association, (2019)SMACK: Semantically Meaningful Adversarial Audio Attack., , , and . USENIX Security Symposium, page 3799-3816. USENIX Association, (2023)Generating Adversarial Examples with Adversarial Networks., , , , , and . IJCAI, page 3905-3911. ijcai.org, (2018)Spatially Transformed Adversarial Examples., , , , , and . ICLR (Poster), OpenReview.net, (2018)Adversarial Sensor Attack on LiDAR-based Perception in Autonomous Driving., , , , , , , , and . ACM Conference on Computer and Communications Security, page 2267-2281. ACM, (2019)PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition., , , , and . CoRR, (2022)CSI: Enhancing the Robustness of 3D Point Cloud Recognition against Corruption., , and . CoRR, (2023)VoxFormer: Sparse Voxel Transformer for Camera-Based 3D Semantic Scene Completion., , , , , , , and . CVPR, page 9087-9098. IEEE, (2023)Exploring the Limits of Domain-Adaptive Training for Detoxifying Large-Scale Language Models., , , , , , , , and . NeurIPS, (2022)