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RobustBench: a standardized adversarial robustness benchmark
[article]
2021
arXiv
pre-print
As a research community, we are still lacking a systematic understanding of the progress on adversarial robustness which often makes it hard to identify the most promising ideas in training robust models. A key challenge in benchmarking robustness is that its evaluation is often error-prone leading to robustness overestimation. Our goal is to establish a standardized benchmark of adversarial robustness, which as accurately as possible reflects the robustness of the considered models within a
arXiv:2010.09670v3
fatcat:bfekmer6xjet5a6lljep5fg3aq