---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: source
    dtype: string
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 4555446.0
    num_examples: 800
  download_size: 4393010
  dataset_size: 4555446.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: apache-2.0
task_categories:
- image-to-text
tags:
- arabic
- ocr
- document-understanding
- multi-modal
---

KITAB-Bench is a comprehensive benchmark for Arabic OCR and document understanding, evaluating performance across multiple domains and tasks, including text recognition, layout detection, table and chart extraction, and more.  It includes 8,809 samples across 9 major domains and features high-quality human-labeled annotations.  This dataset provides image data, source information, and corresponding text transcriptions.


**Please see paper & code for more information:**
- [Project Page](https://mbzuai-oryx.github.io/KITAB-Bench/)
- [GitHub Repository](https://github.com/mbzuai-oryx/KITAB-Bench)
- [Arxiv Paper](https://arxiv.org/abs/2502.14949)