Datasets › DocCVQA

DocCVQA (Document Collection Visual Question Answering)

Introduced by Rubèn Tito et al. in Document Collection Visual Question Answering27 Apr 2021 archive 2025-07-28

DocCVQA is a Document Visual Question Answering dataset, where the questions are posed over a whole collection of 14,362 scanned documents. Therefore, the task can be seen as a retrieval-style evidence seeking task where given a question, the aim is to identify and retrieve all the documents in a large document collection that are relevant to answering this question as well as provide the answer.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 6 papers for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • DocCVQA

1 variant name, as the archive lists them.

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