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Improve dataset card with metadata and description

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This PR improves the dataset card by:

- Adding essential metadata including `task_categories`, `license`, and relevant `tags`.
- Providing a more comprehensive description of the KITAB-Bench dataset.
- Including links to the paper and code repository for easier access to more detailed information.

The existing metadata regarding dataset structure and size is retained as it is useful information.

Files changed (1) hide show
  1. README.md +26 -3
README.md CHANGED
@@ -18,8 +18,31 @@ configs:
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  data_files:
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  - split: train
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  path: data/train-*
 
 
 
 
 
 
 
 
 
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  ---
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- **Please see paper & code for more information:**
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- - https://github.com/mbzuai-oryx/KITAB-Bench
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- - https://arxiv.org/abs/2502.14949
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  data_files:
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  - split: train
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  path: data/train-*
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+ task_categories:
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+ - image-to-text
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+ license: apache-2.0
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+ tags:
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+ - arabic
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+ - ocr
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+ - document-understanding
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+ - multi-domain
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+ - benchmark
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  ---
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+ # KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding
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+ KITAB-Bench is a comprehensive benchmark for evaluating Arabic OCR and document understanding. It covers 9 key tasks across 9 major domains and 36 sub-domains, including text recognition (OCR), layout detection, table recognition, PDF-to-Markdown conversion, chart-to-DataFrame extraction, diagram-to-JSON extraction, and Visual Question Answering (VQA). The dataset includes over 8,809 samples with high-quality human-labeled annotations. Novel evaluation metrics are introduced to accurately assess performance across these diverse tasks.
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+ **Key Features:**
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+ - 9 major domains & 36 sub-domains across 8,809 samples.
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+ - Diverse document types: PDFs, handwritten text, structured tables, financial & legal reports.
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+ - Evaluation across OCR, layout detection, table recognition, chart extraction, & PDF conversion.
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+ - Novel evaluation metrics: MARS, TEDS, SCRM, CODM.
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+ **For more details, including the complete methodology, evaluation metrics, and results, please refer to:**
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+ - **Paper:** [KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding](https://arxiv.org/abs/2502.14949)
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+ - **Code:** [https://github.com/mbzuai-oryx/KITAB-Bench](https://github.com/mbzuai-oryx/KITAB-Bench)
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+ - **Project Page:** [https://mbzuai-oryx.github.io/KITAB-Bench/](https://mbzuai-oryx.github.io/KITAB-Bench/)