---
license: cc-by-nc-4.0
pretty_name: VisualWorldBench-50K
---

# VisualWorldBench-50K

Training dataset for **VisualWorldBench: A Fine-Grained Multi-Task Benchmark for Evaluating Visual World Knowledge in MLLMs**.

**Authors:** Chen Chen, Zheming Liang, Jiaqi Wang.

[Project and code](https://github.com/chenchen0103/VisualWorldBench) · [Evaluation dataset](https://huggingface.co/datasets/orange0318/VisualWorldBench)

The release contains **7,670,789 training records** across MCQ, Open-QA, and grounding, covering **54,434 distinct target names**.

Compared with the data used in the reported experiments, this release includes additional source-level and annotation-quality filtering.

| Task | Complete annotation file | Records |
|---|---|---:|
| MCQ | `annotations/train.mcq.v3.jsonl.gz` | 6,850,706 |
| Open-QA | `annotations/train.open_qa.jsonl.gz` | 385,040 |
| Grounding | `annotations/train.grounding.jsonl.gz` | 435,043 |

The 47 MCQ `part-*` files are subsets covering the first 777,413 records of the complete MCQ file. For the full MCQ set, use `annotations/train.mcq.v3.jsonl.gz` alone.

Each compressed JSONL file contains one training record per line with `messages` and `images`.

MCQ and Open-QA records provide a direct image URL or an official dataset download page in `images`. Records with dataset-page URLs also include `path`, which locates the image within the extracted dataset. Obtain these images under the original providers' access conditions and replace `images` with local file paths before training.

Grounding records use image paths relative to the dataset directory. The **428,501 grounding images** are included in `image_shards/grounding-*.tar.gz`. Extract all grounding archives from the dataset directory:

```bash
for archive in image_shards/grounding-*.tar.gz; do
  tar -xzf "$archive" -C .
done
```

MCQ includes both ordinary and reasoning responses. Open-QA responses use `<think>...</think>` and `<answer>...</answer>`. Grounding responses contain bounding boxes in integer normalized `[x1, y1, x2, y2]` coordinates, as specified by each prompt.

Original training annotations are licensed under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). This license applies to the annotations only; third-party images remain subject to their respective licenses and terms.

If you encounter any issues downloading the images, please contact the authors.