--- configs: - config_name: default data_files: - split: train path: data/train-* license: apache-2.0 dataset_info: features: - name: image dtype: image - name: image_id dtype: string - name: style dtype: string - name: category dtype: string - name: source dtype: string - name: text list: string - name: word_count list: int32 - name: total_words dtype: int32 - name: bboxes list: list: int32 splits: - name: train num_bytes: 402789351 num_examples: 1272 download_size: 399125040 dataset_size: 402789351 ---

DuwatBench: Bridging Language and Visual Heritage through an Arabic Calligraphy Benchmark for Multimodal Understanding [EACL 2026 (Main)🔥]

[Shubham Patle](https://github.com/shubhamrpatle) 1*   [Sara Ghaboura](https://huggingface.co/SLMLAH) 1*   [Hania Tariq](https://huggingface.co/) 2   [Mohammad Usman Khan](https://huggingface.co/) 3  
[Omkar Thawakar](https://omkarthawakar.github.io) 1   [Rao M. Anwer](https://scholar.google.com/citations?hl=en&user=_KlvMVoAAAAJ) 1  [Salman Khan](https://scholar.google.com/citations?hl=en&user=M59O9lkAAAAJ) 1,4

1Mohamed bin Zayed University of AI    2NUCES    3NUST    4Australian National University

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*Equal Contribution

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## Latest Updates 🔥🔥 **[04 Jan 2026]** 🔥🔥 DuwatBench accepted to EACL 2026 Main track.
🔥 **[22 Jan 2026]** DuwatBench, the Arabic Calligraphy Benchmark for Multimodal Understanding is released.
🤗 **[23 Jan 2026]** DuwatBench dataset available on [HuggingFace](https://huggingface.co/datasets/MBZUAI/TimeTravel).
--- ## ✨ Overview
**DuwatBench** is a comprehensive benchmark for evaluating LMMs on Arabic calligraphy recognition. Arabic calligraphy represents one of the richest visual traditions of the Arabic language, blending linguistic meaning with artistic form. DuwatBench addresses the gap in evaluating how well modern AI systems can process stylized Arabic text.
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Fig.1.a. Proportional breakdown of calligraphic styles
in the DuwatBench dataset
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Fig.1.b.Proportional breakdown of textual categories,
covering religious and non-religious themes
| |:-------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------:| | | |

--- ## 🌟 Key Features ### **Key Features of TimeTravel** - **1,272 curated samples** spanning 6 classical and modern calligraphic styles - **Over 9.5k word instances with approximately 1,475 unique words** spanning religious and cultural domains - **Bounding box annotations** for detection-level evaluation - **Full text transcriptions** with style and theme labels - **Complex artistic backgrounds** preserving real-world visual complexity --- ## 🏗️ DuwatBench Creation Pipeline The DuwatBench dataset follows a structured pipeline to ensure the accuracy, completeness, and contextual richness by style and category.

pipeline

Figure 2. End-to-end pipeline for constructing DuwatBench, from data collection and manual transcription with bounding boxes to multi-tier verification and style/theme aggregation.
--- ## ✒️ Calligraphic Styles | Style | Arabic | Description | |-------|--------|-------------| | **Thuluth** | الثلث | Ornate script used in mosque decorations | | **Diwani** | الديواني | Flowing Ottoman court script | | **Naskh** | النسخ | Standard readable script | | **Kufic** | الكوفي | Geometric angular early Arabic script | | **Ruq'ah** | الرقعة| Modern everyday handwriting | | **Nasta'liq** | النستعليق| Persian-influenced flowing script | --- ## 🧐 DuwatBench Dataset Examples

sample

Figure 2. End-to-end pipeline for constructing DuwatBench, from data collection and manual transcription with bounding boxes to multi-tier verification and style/theme aggregation.
--- ## 🔍 Qualitative Evaluation and Results

pipeline

Figure 3. Qualitative results comparing open- and closed-source models on DuwatBench calligraphy samples.
--- ## 📚 Citation If you use DuwatBench dataset in your research, please consider citing: ```bibtex @misc{patle2026duwatbenchbridginglanguagevisual, title={DuwatBench: Bridging Language and Visual Heritage through an Arabic Calligraphy Benchmark for Multimodal Understanding}, author={Shubham Patle and Sara Ghaboura and Hania Tariq and Mohammad Usman Khan and Omkar Thawakar and Rao Muhammad Anwer and Salman Khan}, year={2026}, eprint={2601.19898}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2601.19898}, } ``` --- ## ⚖️ License This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details. The dataset images are sourced from public digital archives and community repositories under their respective licenses. --- ## 🙏 Acknowledgments - Digital archives: [Library of Congress](https://www.loc.gov/collections/), [NYPL Digital Collections](https://digitalcollections.nypl.org/) - Community repositories: [Calligraphy Qalam](https://calligraphyqalam.com/), [Free Islamic Calligraphy](https://freeislamiccalligraphy.com/), [Pinterest](https://www.pinterest.com/) - Annotation tool: [MakeSense.ai](https://www.makesense.ai/) - Arabic NLP tools: [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) --- ## 📧 Contact For questions or issues, please: - Open an issue on [GitHub](https://github.com/mbzuai-oryx/DuwatBench/issues) - Contact the authors at: {shubham.patle, sara.ghaboura, omkar.thawakar}@mbzuai.ac.ae ---