---
dataset_info:
  features:
  - name: questionId
    dtype: int32
  - name: question
    dtype: string
  - name: question_types
    list: string
  - name: image
    dtype: image
  - name: docId
    dtype: int32
  - name: ucsf_document_id
    dtype: string
  - name: ucsf_document_page_no
    dtype: string
  - name: answers
    list: string
  splits:
  - name: train
    num_bytes: 5658303093.631
    num_examples: 39463
  - name: validation
    num_bytes: 2532362556.066
    num_examples: 5349
  - name: test
    num_bytes: 2500321215.732
    num_examples: 5188
  download_size: 9591606021
  dataset_size: 10690986865.428999
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---
<div align="center">

# Neural Metrics · Asking documents questions, and grading the answers.

<img src="https://img.shields.io/badge/Neural%20Metrics-document%20extraction-4F46E5?style=for-the-badge" alt="Neural Metrics" />
<img src="https://img.shields.io/badge/fork%20of-HuggingFaceM4%2FDocumentVQA-2563EB?style=flat-square" alt="fork" />

</div>

Document visual question answering: given a page image and a natural-language question, produce the answer. It measures whether a model genuinely read the layout or merely pattern-matched the text.

**We use it for:** evaluating question-answering over extracted documents - catching models that read text but misread structure.

> ### Attribution
> This is an **unmodified fork** of [`HuggingFaceM4/DocumentVQA`](https://huggingface.co/datasets/HuggingFaceM4/DocumentVQA), created by the [Qwen team](https://huggingface.co/Qwen).
> All weights, files and behaviour are identical to upstream — we rehost it so our experiments stay
> reproducible and version-pinned. The original license and all credit remain with the Qwen team.
> If you want the canonical dataset, please use [the original](https://huggingface.co/datasets/HuggingFaceM4/DocumentVQA).

---

<details>
<summary><b>Original dataset card from HuggingFaceM4/DocumentVQA</b> (click to expand)</summary>



</details>