Datasets › GD-VCR
GD-VCR
Geo-Diverse Visual Commonsense Reasoning (GD-VCR) is a new dataset to test vision-and-language models' ability to understand cultural and geo-location-specific commonsense.
Image source: https://arxiv.org/pdf/2109.06860v1.pdf
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 | ||||
|---|---|---|---|---|---|---|
| Visual Commonsense Reasoning | GD-VCR | Human Accuracy 88.84 | Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning | wadeyin9712/gd-vcr | 4 | 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 6. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning | 1 | 4 | 14 Sep 2021 | ran 0 of 9 samples (9 unverified) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Unknown
Modalities archive 2025-07-28
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- GD-VCR
1 variant name, as the archive lists them.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections