{"url":"/dataset/q-bench","name":"Q-Bench","full_name":null,"description_markdown":"The Q-Bench includes three realms for low-level vision: perception (A1), description (A2), and assessment (A3). \r\n- For perception (A1) /description (A2), we collect two benchmark datasets LLVisionQA/LLDescribe.\r\n- For assessment (A3), as we use public datasets, we provide an abstract evaluation code for arbitrary MLLMs for anyone to test.","description_withheld":null,"homepage":"https://q-future.github.io/Q-Bench","introduced_date":"2023-09-25","introduced_date_note":null,"introduced_by":{"paper":"/paper/q-bench-a-benchmark-for-general-purpose","title":"Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision","first_author":"HaoNing Wu","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Q-Bench"],"data_loaders":[],"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."}