Datasets:

cubec
/

spatialtunnel

configs:
  - config_name: size_variation
    data_files: size_variation.tsv
    sep: "\t"
    default: true
  - config_name: phase_variation
    data_files: phase_variation.tsv
    sep: "\t"
  - config_name: contrastive_probing
    data_files: contrastive_probing.tsv
    sep: "\t"

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:

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.

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},
}