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Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation.

, and . NIPS, page 2266-2276. (2017)

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RobustBench: a standardized adversarial robustness benchmark., , , , , , , and . NeurIPS Datasets and Benchmarks, (2021)SGD with Large Step Sizes Learns Sparse Features., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 903-925. PMLR, (2023)Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs., , , , , , and . CoRR, (2024)Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks., , and . CoRR, (2024)Provably robust boosted decision stumps and trees against adversarial attacks., and . NeurIPS, page 12997-13008. (2019)The Effects of Overparameterization on Sharpness-aware Minimization: An Empirical and Theoretical Analysis., , , and . CoRR, (2023)Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning., , , and . ICML, OpenReview.net, (2024)ARIA: Adversarially Robust Image Attribution for Content Provenance., , , , , , and . CVPR Workshops, page 33-43. IEEE, (2022)Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search., , , and . ECCV (23), volume 12368 of Lecture Notes in Computer Science, page 484-501. Springer, (2020)Square Attack: a query-efficient black-box adversarial attack via random search., , , and . CoRR, (2019)