SERGE / README.md
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---
license: other
license_name: mixed-original-licenses
license_link: https://github.com/brendenlake/omniglot
task_categories:
- image-classification
- visual-question-answering
language:
- en
tags:
- omniglot
- pacs
- vision-language
- visual-invariance
- geometric-reasoning
- domain-generalization
- arxiv:2604.01848
- serge
pretty_name: SERGE
size_categories:
- 1K<n<10K
---
# SERGE (**SE**mantic **R**ichness & **G**eometric **E**valuation)
SERGE is the evaluation dataset released with the paper [*Semantic Richness or Geometric Reasoning? The Fragility of VLM's Visual Invariance*](https://arxiv.org/abs/2604.01848). It contains the canonical (untransformed) images used to test whether VLMs judge object identity under rotation, scale, and identity transformations through geometric reasoning or through familiarity with semantically rich content.
- **Paper:** [arXiv:2604.01848](https://arxiv.org/abs/2604.01848)
- **Project page:** [xthomasbu.github.io/visual_invariance](https://xthomasbu.github.io/visual_invariance/)
- **Code:** [github.com/XThomasBU/semantic_richness](https://github.com/XThomasBU/semantic_richness)
## Dataset overview
| Dataset | # Samples | Description |
| --- | --- | --- |
| Omniglot | 1,623 | Handwritten characters across 50 scripts |
| Times New Roman | 52 | Printed English alphabet (A–Z, a–z) |
| Handwritten English | 52 | Handwritten English alphabet |
| PACS | 800 | 4 domains × 200 images each |
Together these span a semantic-richness spectrum used in the paper: symbolic sketches (Omniglot) → semantic sketches (Handwritten English, Times New Roman) → natural photos and art (PACS).
### Directory layout
```text
omniglot/images_all/{Script}/characterXX/*.png # 50 official scripts + hand_english
times_new_roman/characterXX/image.png
pacs/{domain}_{label}_{hf_index}.png
manifest.json # per-script / per-domain counts
```
`hand_english` (the Handwritten English row above) is stored under `omniglot/images_all/hand_english` alongside the 50 official Omniglot scripts. `pacs` filenames encode metadata, e.g. `art_painting_0_101.png` → domain=`art_painting`, label=`0` (dog), source index=`101`.
## Loading the dataset
```python
from huggingface_hub import snapshot_download
from datasets import load_dataset
local_dir = snapshot_download(repo_id="XThomasBU/SERGE", repo_type="dataset")
omniglot = load_dataset("imagefolder", data_dir=f"{local_dir}/omniglot/images_all", split="train")
times_new_roman = load_dataset("imagefolder", data_dir=f"{local_dir}/times_new_roman", split="train")
pacs = load_dataset("imagefolder", data_dir=f"{local_dir}/pacs", split="train")
```
## Citation
If you use SERGE, please cite the paper:
```bibtex
@article{qiu2026semantic,
title={Semantic Richness or Geometric Reasoning? The Fragility of VLM's Visual Invariance},
author={Qiu, Jason and Meurer, Zachary and Thomas, Xavier and Ghadiyaram, Deepti},
journal={arXiv preprint arXiv:2604.01848},
year={2026}
}
```
and the original source datasets:
> Brenden M. Lake, Ruslan Salakhutdinov, and Joshua B. Tenenbaum. Human-level concept learning through probabilistic program induction. *Science*, 350(6266):1332–1338, 2015. doi: 10.1126/science.aab3050. URL https://www.science.org/doi/abs/10.1126/science.aab3050.
>
> Sujay Mann. Handwritten english characters and digits, 2024. URL https://www.kaggle.com/datasets/sujaymann/handwritten-english-characters-and-digits. Accessed: 2026-03-29.
>
> Samuel Yu, Peter Wu, Paul Pu Liang, Ruslan Salakhutdinov, and Louis-Philippe Morency. Pacs: A dataset for physical audiovisual commonsense reasoning, 2022. URL https://arxiv.org/abs/2203.11130.
>
> Stanley Morison and Victor Lardent. Times new roman. https://en.wikipedia.org/wiki/Times_New_Roman, 1932. Typeface originally commissioned for The Times newspaper. Accessed: 2026-03-30.