WildTableBench / README.md
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update: add arxiv paper link and full citation
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---
license: cc-by-4.0
task_categories:
- visual-question-answering
language:
- en
tags:
- table-understanding
- multimodal
- benchmark
pretty_name: WildTableBench
size_categories:
- 1K<n<10K
---
# WildTableBench
[[Paper](https://arxiv.org/abs/2605.01018)] [[GitHub](https://github.com/hjzhe/WildTableBench)]
**WildTableBench** is a benchmark for evaluating multimodal foundation models on table understanding in the wild.
- **402 real-world table images** collected from diverse domains
- **928 questions** across 5 categories and 17 subtypes
- Covers numerical reasoning, verification, cell locating, structural understanding, and more
## Dataset Structure
```
WildTableBench/
├── metadata.csv # 928 questions with labels
└── images/ # 402 table images (1.jpg … 402.jpg)
```
### `metadata.csv` columns
| Column | Description |
|---|---|
| `file_name` | Relative path to the image (e.g. `images/1.jpg`) |
| `image_id` | Image index (1–402) |
| `index` | Question index within the image (1, 2, …) |
| `uuid` | Unique question ID (e.g. `wtb_001_q1`) |
| `question` | Question text |
| `category` | Category ID (C1–C5) |
| `category_name` | Category name |
| `subtype_id` | Subtype ID (e.g. `C2-C`) |
| `subtype_name` | Subtype name |
| `ground_truth` | Ground truth answer |
## Question Categories
| ID | Name | Subtypes |
|---|---|---|
| C1 | Cell-Level | Transcription, Cell Locating, Semantic Lookup & Struct., Excel Formula |
| C2 | Numerical | Basic Numerical, Conditional Numerical, Multi-step Conditional, Ranking |
| C3 | Verification | Value Verification, Aggregate Verification, Conditional Verification |
| C4 | Hypothetical | Hypothetical Condition, Value Modification, Row Operation |
| C5 | Color | Color Identification, Color-based Counting, Color-based Reasoning |
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("jzhuang/WildTableBench")
```
## Citation
```bibtex
@article{huang2025wildtablebench,
title={WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild},
author={Junzhe Huang and Xiaoxiao Sun and Yan Yang and Yuxuan Hou and Ruotian Zhang and Sirui Li and Hehe Fan and Serena Yeung-Levy and Xin Yu},
journal={arXiv preprint arXiv:2605.01018},
year={2025},
}
```