{"url":"/dataset/webqa","name":"WebQA","full_name":null,"description_markdown":"WebQA, is a new benchmark for multimodal multihop reasoning in which systems are presented with the same style of data as humans when searching the web: Snippets and Images. The system must then identify which information is relevant across modalities and combine it with reasoning to answer the query. Systems will be evaluated on both the correctness of their answers and their sources.","description_withheld":null,"homepage":"https://webqna.github.io/","introduced_date":"2021-09-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/webqa-multihop-and-multimodal-qa","title":"WebQA: Multihop and Multimodal QA","first_author":"Yingshan Chang","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Visual Question Answering (VQA)","url":"/task/visual-question-answering","datasets_with_task":"/datasets/task/visual-question-answering"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["WebQA"],"data_loaders":[],"num_papers_in_archive":43,"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."}