Datasets › WIT

WIT (Wikipedia-based Image Text)

Introduced by Krishna Srinivasan et al. in WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning2 Mar 2021 archive 2025-07-28

Wikipedia-based Image Text (WIT) Dataset is a large multimodal multilingual dataset. WIT is composed of a curated set of 37.6 million entity rich image-text examples with 11.5 million unique images across 108 Wikipedia languages. Its size enables WIT to be used as a pretraining dataset for multimodal machine learning models.

Key Advantages

A few unique advantages of WIT:

  • The largest multimodal dataset (time of this writing) by the number of image-text examples.
  • A massively multilingual (first of its kind) with coverage for over 100+ languages.
  • A collection of diverse set of concepts and real world entities.
  • Brings forth challenging real-world test sets.

Benchmarks archive 2025-07-28

All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

First row (archive order)PaperCode
Image Retrieval WIT WIT-ALL R@1 0.346 WIT: Wikipedia-based Image Text Dataset for Multimodal... google-research-datasets/wit +2 2 Compare

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 79. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning 3 2 2 Mar 2021 not harvested

Dataset loaders archive 2025-07-28

4 loaders as listed in the archive; links are outbound and not re-checked here.

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

  • WIT

1 variant name, as the archive lists them.

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