{"url":"/dataset/robustbench","name":"RobustBench","full_name":null,"description_markdown":"**RobustBench** is a benchmark of adversarial robustness, which as accurately as possible reflects the robustness of the considered models within a reasonable computational budget. To this end, we start by considering the image classification task and introduce restrictions (possibly loosened in the future) on the allowed models.","description_withheld":null,"homepage":"https://github.com/RobustBench/robustbench","introduced_date":"2020-10-19","introduced_date_note":null,"introduced_by":{"paper":"/paper/robustbench-a-standardized-adversarial","title":"RobustBench: a standardized adversarial robustness benchmark","first_author":"Francesco Croce","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["RobustBench"],"data_loaders":[],"num_papers_in_archive":133,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}