SpatialTunnel

SpatialTunnel is a Blender-rendered diagnostic dataset for studying how vision-language models represent spatial relations internally. It was introduced in Why Far Looks Up: Probing Spatial Representation in Vision-Language Models (arXiv:2605.30161).

Related resources:

• Project page
• Contrastive-probing code
• SpatialTunnel generation code

Dataset Configs

Config	File	Rows	Description
size_variation	size_variation.tsv	1,100	Apparent-size questions under controlled object-size variation.
phase_variation	phase_variation.tsv	3,072	Distance questions with controlled angular-position variation.
contrastive_probing	contrastive_probing.tsv	1,200	Balanced spatial-relation questions for contrastive probing.

Format

All configs are tab-separated files with the same columns:

Column	Description
index	Row index within the selected config.
image	Base64-encoded PNG image.
question	Spatial question to ask the model.
answer	Ground-truth answer for the row.

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Citation

If you use this dataset, please cite our paper.

@article{min2026whyfarlooksup,
  title   = {Why Far Looks Up: Probing Spatial Representation in Vision-Language Models},
  author  = {Min, Cheolhong and Jung, Jaeyun and Lee, Daeun and Jeon, Hyeonseong and
             Su, Yu and Tremblay, Jonathan and Song, Chan Hee and Park, Jaesik},
  journal = {arXiv preprint arXiv:2605.30161},
  year    = {2026},
}