Datasets › RealWorldQA
RealWorldQA
RealWorldQA is a benchmark designed to evaluate the real-world spatial understanding capabilities of multimodal AI models. It assesses how well these models comprehend physical environments. The benchmark consists of over 700 images, each accompanied by a question and a verifiable answer. These images are drawn from various real-world scenarios, including those captured from vehicles. The goal is to advance AI models' understanding of our physical world.
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) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Spatial Reasoning | RealWorldQA | no rows | — | — | 0 | Compare |
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset.
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
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- RealWorldQA
1 variant name, as the archive lists them.
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