{"url":"/dataset/viquae","name":"ViQuAE","full_name":null,"description_markdown":"ViQuAE is a dataset for KVQAE (Knowledge-based Visual Question Answering about named Entities), a task which consists in answering questions about named entities grounded in a visual context  using a Knowledge Base. It is the first KVQAE dataset to cover a wide range of entity types (e.g. persons, landmarks, and products). We argue that KVQAE is a clear, well-defined task that can be evaluated easily, making it suitable to track the progress of multimodal entity representation’s quality. Multimodal entity representation is a central issue that will allow to make human-machine interactions more natural. For example, while watching a movie, one might wonder ‘‘Where did I already see this actress?’’ or ‘‘Did she ever win an Oscar?’’","description_withheld":null,"homepage":"https://github.com/PaulLerner/ViQuAE","introduced_date":"2022-07-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/viquae-a-dataset-for-knowledge-based-visual-1","title":"ViQuAE, a Dataset for Knowledge-based Visual Question Answering about Named Entities","first_author":"Paul Lerner","url":null},"license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"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"},{"name":"Factual Visual Question Answering","url":"/task/factual-visual-question-answering","datasets_with_task":"/datasets/task/factual-visual-question-answering"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["ViQuAE"],"data_loaders":[],"num_papers_in_archive":13,"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."}