---
title: "Who cites KITAB-Bench: A Comprehensive — 9 citing papers"
description: "9 papers of the Elamur Research library cite «KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document…"
canonical: "https://research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [KITAB-Bench: A Comprehensive Multi-Domain…](https://md.research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/) / cited by

# Who cites «KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding»

9 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding»](https://md.research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/)

1. **[SAHM: A Benchmark for Arabic Financial and Shari'ah-Compliant Reasoning](https://md.research.elamur.ai/free/en/papers/elbadry-2026-sahm-benchmark-arabic-financial-shari/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rania Elbadry, Sarfraz Ahmad, Ahmed Heakl, et al.*2026 · 4 citations*
2. [**Baseer: A Vision-Language Model for Arabic Document-to-Markdown OCR arXiv:2509.18174**Khalil Hennara, Muhammad Hreden, Mohamed Motasim Hamed, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/hennara-2025-baseer-vision-language-model-arabic/)
3. **[POLYCHARTQA: Benchmarking Large Vision-Language Models with Multilingual Chart Question Answering](https://md.research.elamur.ai/free/en/papers/xu-2026-polychartqa-benchmarking-large-vision-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichen Xu, Liangyu Chen, Liang Zhang, et al.*2026 · 2 citations*
4. **[OCRTurk: A Comprehensive OCR Benchmark for Turkish](https://md.research.elamur.ai/free/en/papers/yilmaz-2026-ocrturk-comprehensive-ocr-benchmark-turkish/) [Workshop Natural Language Processing for Turkic Languages](https://md.research.elamur.ai/free/en/venues/sigturk/)**Deniz Yılmaz, Evren Ayberk Munis, Cagri Toraman, et al.*2026 · 1 citation*
5. [**Cross-Lingual SynthDocs: A Large-Scale Synthetic Corpus for Any to Arabic OCR and Document Understanding arXiv:2511.04699**Haneen Al-Homoud; Asma Ibrahim; Murtadha Al-Jubran; Fahad Al-Otaibi; Yazeed Al-Harbi; Daulet Toibazar; Kesen Wang;, Pedro J. Moreno*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/al-homoud-2025-cross-lingual-synthdocs-large-scale/)
6. [**AraMS-28k: The Largest Publicly Released Line-Level Dataset of Historical Arabic Manuscripts with Margin and Insertion-Anchor Annotations arXiv:2608.26921**Mohamed Guechaoui, Mohamed Diaa Zellagui, Souleyman Chaib, et al.*2026*](https://md.research.elamur.ai/free/en/papers/guechaoui-2026-arams-28k-largest-publicly-released/)
7. **[InkSight: Towards AI-Aided Historical Manuscript Analysis](https://md.research.elamur.ai/free/en/papers/sakhovskiy-2026-inksight-ai-aided-historical-manuscript/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Andrey Sakhovskiy, Ivan Ulitin, Emilia Bojarskaja, et al.*2026*
8. **[-SEA³-QA: A Fully Automated Self-Evolving, Adversarial Workflow for Arabic Long-Context Question-Answer Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-mathbfa-sea-3-mathbfl-qa/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Kesen Wang, Daulet Toibazar, Pedro J Moreno Mengibar*2025*

1 more paper of our library cites it; it has no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/heakl-2025-kitab-bench-comprehensive-multi-domain/) — KITAB-Bench: A Comprehensive Multi-Domain Benchmark for Arabic OCR and Document Understanding