Add task category metadata and sample usage

This PR improves the dataset card by:
- Adding the `image-text-to-text` task category to the YAML metadata.
- Including a "Sample Usage" section with instructions on how to download the dataset files using the `huggingface-cli`, as found in the official GitHub repository.
- Refining the dataset description based on the paper's abstract to clarify its role as a diagnostic tool for spatial reasoning in Vision-Language Models (VLMs).
- Preserving existing data configurations for correct loading of the TSV files.

README.md

@@ -10,17 +10,21 @@ configs:
 - config_name: contrastive_probing
   data_files: contrastive_probing.tsv
   sep: "\t"
+task_categories:
+- image-text-to-text
 ---
 
 # 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](https://arxiv.org/abs/2605.30161)).
+SpatialTunnel is a Blender-rendered diagnostic dataset for studying how vision-language models (VLMs) represent spatial relations internally. It was introduced in the paper: **[Why Far Looks Up: Probing Spatial Representation in Vision-Language Models](https://huggingface.co/papers/2605.30161)**.
 
-Related resources:
+The dataset is designed to isolate spatial shortcut biases (like the perspective bias where "higher in image means farther away") by removing background and perspective correlations present in natural images.
 
-- [Project page](https://cheolhong0916.github.io/whyfarlooksup.github.io/)
-- [Contrastive-probing code](https://github.com/cheolhong0916/contrastive-probing)
-- [SpatialTunnel generation code](https://github.com/cube-c/spatialtunnel-dataset-gen)
+### Resources
+
+- **Project page:** [https://cheolhong0916.github.io/whyfarlooksup.github.io/](https://cheolhong0916.github.io/whyfarlooksup.github.io/)
+- **Contrastive-probing code:** [https://github.com/cheolhong0916/contrastive-probing](https://github.com/cheolhong0916/contrastive-probing)
+- **SpatialTunnel generation code:** [https://github.com/cube-c/spatialtunnel-dataset-gen](https://github.com/cube-c/spatialtunnel-dataset-gen)
 
 ## Dataset Configs
 
@@ -32,7 +36,7 @@ Related resources:
 
 ## Format
 
-All configs are tab-separated files with the same columns:
+All configs are tab-separated files with the following columns:
 
 | Column | Description |
 |---|---|
@@ -41,11 +45,19 @@ All configs are tab-separated files with the same columns:
 | `question` | Spatial question to ask the model. |
 | `answer` | Ground-truth answer for the row. |
 
+## Sample Usage
+
+You can download specific parts of the benchmark using the Hugging Face CLI:
+
+```bash
+huggingface-cli download cubec/spatialtunnel contrastive_probing.tsv --repo-type dataset --local-dir ./data
+```
+
 ---
 
 ## Citation
 
-If you use this dataset, please cite our paper.
+If you use this dataset, please cite our paper:
 
 ```bibtex
 @article{min2026whyfarlooksup,
@@ -55,4 +67,4 @@ If you use this dataset, please cite our paper.
   journal = {arXiv preprint arXiv:2605.30161},
   year    = {2026},
 }
-```
+```