Improve dataset card with description, links, and metadata

This PR improves the dataset card by:

- Adding a detailed description of the KITAB-Bench dataset.
- Including links to the paper and code repository.
- Specifying the `task_categories` as `table-question-answering`.
- Adding the license information.
- Retaining the existing feature information.

README.md

@@ -18,7 +18,25 @@ configs:
   data_files:
   - split: train
     path: data/train-*
+task_categories:
+- table-question-answering
+license: apache-2.0
 ---
+
+# KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding
+
+KITAB-Bench is a comprehensive benchmark for evaluating Arabic OCR and document understanding capabilities.  It covers nine major domains and 36 sub-domains across 8,809 samples, including diverse document types like PDFs, handwritten text, structured tables, and financial & legal reports.  The benchmark evaluates performance across various tasks, including OCR, layout detection, table recognition, chart extraction, and PDF conversion.  Novel evaluation metrics are introduced to ensure rigorous assessment across multiple dimensions.
+
+**Key Highlights:**
+
+* 9 major domains & 36 sub-domains across 8,809 samples.
+* Diverse document types: PDFs, handwritten text, structured tables, financial & legal reports.
+* Strong baselines: Benchmarked against Tesseract, GPT-4o, Gemini, Qwen, and more.
+* Novel evaluation metrics: Markdown Recognition (MARS), Table Edit Distance (TEDS), Chart Data Extraction (SCRM).
+
+
 **Please see paper & code for more information:**
-- https://github.com/mbzuai-oryx/KITAB-Bench
-- https://arxiv.org/abs/2502.14949
+
+- [Paper](https://arxiv.org/abs/2502.14949)
+- [Code](https://github.com/mbzuai-oryx/KITAB-Bench)
+- [Project Page](https://mbzuai-oryx.github.io/KITAB-Bench/)