{"url":"/dataset/urbancars","name":"UrbanCars","full_name":null,"description_markdown":"UrbanCars facilitates multi-shortcut learning under the controlled setting with two shortcuts—background and co-occurring object. The task is classifying the car body type into two categories: *urban* car and *country* car. The dataset contains three splits: training, validation, and testing. In the training set, two shortcuts spuriously correlate with the car body type. Both validation and testing sets are balanced, i.e., no spurious correlations. The validation set is used for model selection, and the testing set evaluates the mitigation of two shortcuts.","description_withheld":null,"homepage":"https://github.com/facebookresearch/Whac-A-Mole","introduced_date":"2022-12-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-whac-a-mole-dilemma-shortcuts-come-in","title":"A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others","first_author":"Zhiheng Li","url":null},"license":{"name":"CC BY-NC","url":"https://github.com/facebookresearch/Whac-A-Mole/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Out-of-Distribution Generalization","url":"/task/out-of-distribution-generalization","datasets_with_task":"/datasets/task/out-of-distribution-generalization"}],"languages":[],"variants":["UrbanCars"],"data_loaders":[{"repo":"https://github.com/facebookresearch/Whac-A-Mole","url":"https://github.com/facebookresearch/Whac-A-Mole","frameworks":["pytorch"]}],"num_papers_in_archive":26,"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."}