{"url":"/dataset/comtqa","name":"ComTQA","full_name":null,"description_markdown":"The **ComTQA dataset** is a visual table question answering benchmark. It includes images collected from **FinTabNet** and **PubTables-1M**, comprising a total of **9,070 QA pairs** with **1,591 images**. The dataset is designed to address tasks related to table question answering and is available in English. It falls under the size category of **1K<n<10K** and is licensed under **cc-by-nc-4.0**¹.\r\n\r\nThis dataset is particularly useful for developing and testing algorithms that can interpret and answer questions based on tabular data. It's a valuable resource for researchers and practitioners in the field of machine learning and natural language processing, especially those focusing on the intersection of visual data interpretation and question answering systems¹.\r\n\r\n(1) ByteDance/ComTQA · Datasets at Hugging Face. https://huggingface.co/datasets/ByteDance/ComTQA.\r\n(2) ComQA Dataset | Papers With Code. https://paperswithcode.com/dataset/comqa.\r\n(3) COMETA: the corpus of online medical entities - GitHub. https://github.com/cambridgeltl/cometa.\r\n(4) COMETA Dataset | Papers With Code. https://paperswithcode.com/dataset/cometa.","description_withheld":null,"homepage":"https://huggingface.co/datasets/ByteDance/ComTQA","introduced_date":"2024-06-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/tabpedia-towards-comprehensive-visual-table","title":"TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy","first_author":"Weichao Zhao","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["ComTQA"],"data_loaders":[],"num_papers_in_archive":1,"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."}