{"url":"/dataset/clevr-ref","name":"CLEVR-Ref+","full_name":null,"description_markdown":"CLEVR-Ref+ is a synthetic diagnostic dataset for referring expression comprehension. The precise locations and attributes of the objects are readily available, and the referring expressions are automatically associated with functional programs. The synthetic nature allows control over dataset bias (through sampling strategy), and the modular programs enable intermediate reasoning ground truth without human annotators. \r\n\r\nSource: [CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions](https://arxiv.org/pdf/1901.00850v2.pdf)","description_withheld":null,"homepage":"https://cs.jhu.edu/~cxliu/2019/clevr-ref+","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/clevr-ref-diagnosing-visual-reasoning-with","title":"CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions","first_author":"Runtao Liu","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Question Answering","url":"/task/question-answering","datasets_with_task":"/datasets/task/question-answering"},{"name":"Visual Question Answering (VQA)","url":"/task/visual-question-answering","datasets_with_task":"/datasets/task/visual-question-answering"},{"name":"Referring Expression Segmentation","url":"/task/referring-expression-segmentation","datasets_with_task":"/datasets/task/referring-expression-segmentation"},{"name":"Visual Reasoning","url":"/task/visual-reasoning","datasets_with_task":"/datasets/task/visual-reasoning"},{"name":"Referring Expression Comprehension","url":"/task/referring-expression-comprehension","datasets_with_task":"/datasets/task/referring-expression-comprehension"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["CLEVR-Ref+"],"data_loaders":[],"num_papers_in_archive":17,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/referring-expression-segmentation-on-clevr","task":"Referring Expression Segmentation","dataset_variant":"CLEVR-Ref+","rows":1,"metrics":["IoU"],"first_row_in_archive_order":{"model":"IEP-Ref (700K prog.)","paper":"/paper/clevr-ref-diagnosing-visual-reasoning-with","metrics":{"IoU":"80.6"},"code_links":[{"title":"ruotianluo/iep-ref","url":"https://github.com/ruotianluo/iep-ref"},{"title":"arjunakula/neurips2021","url":"https://github.com/arjunakula/neurips2021"},{"title":"byahn2/clevr_ref","url":"https://github.com/byahn2/clevr_ref"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/clevr-ref-diagnosing-visual-reasoning-with","title":"CLEVR-Ref+: Diagnosing Visual Reasoning with Referring Expressions","date":"2019-01-03","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":4,"samples_unverified":1,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":5,"samples_ran":4,"samples_unverified":1,"pointer_only_for_licence":5,"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."}