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---
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task_categories:
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- visual-question-answering
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language:
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- ar
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size_categories:
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- 100K<n<1M
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---
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# 💎 Full Pearl Dataset |
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This repository contains the full, unreviewed dataset comprising 309K multimodal examples. This data was generated automatically using the agentic pipeline developed for the **Pearl** project, as described in our paper. |
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**Disclaimer:** This is the raw, synthetic data that has **not** been subject to human review. It was generated as part of the data creation process and is released for research purposes. It may contain noise, errors, or inconsistencies. For the high-quality, human-reviewed benchmarks, please see the links below. |
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## Download |
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The full dataset (309K examples) is hosted on Google Drive: |
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* **Google Drive:** [https://drive.google.com/drive/folders/1awP5ONLRz2IYRYzWSymoR16QBkP3l3HK?usp=sharing](https://drive.google.com/drive/folders/1awP5ONLRz2IYRYzWSymoR16QBkP3l3HK?usp=sharing) |
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### Dataset Contents |
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The dataset is split into multiple `.zip` files: |
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* **JSON Data (`pearl_part_XX.zip`):** These files (e.g., `pearl_part_01.zip`) contain the 309K synthetic multimodal examples (captions, questions, and answers) in JSON format. |
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* **Image Data (`images_part_X.zip`):** These files (e.g., `images_part_1.zip`) contain the corresponding images. |
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You will need to download all parts and unzip them to use the full dataset. |
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## Related Pearl Resources |
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* **Official Website:** [https://pearl.dlnlp.ai/](https://pearl.dlnlp.ai/) |
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* **Human-Reviewed Benchmarks (Hugging Face):** [https://huggingface.co/collections/UBC-NLP/pearl](https://huggingface.co/collections/UBC-NLP/pearl) |
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* **Paper (arXiv):** [Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset](https://arxiv.org/abs/2505.21979) |
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## Citation |
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If you use this dataset or the accompanying benchmarks, please cite our paper: |
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```bibtex |
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@inproceedings{alwajih-etal-2025-pearl, |
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title = "Pearl: A Multimodal Culturally-Aware {A}rabic Instruction Dataset", |
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author = "Alwajih, Fakhraddin and |
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Magdy, Samar M. and |
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El Mekki, Abdellah and |
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Nacar, Omer and |
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Nafea, Youssef and |
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Abdelfadil, Safaa Taher and |
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Yahya, Abdulfattah Mohammed and |
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Luqman, Hamzah and |
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Almarwani, Nada and |
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Aloufi, Samah and |
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Qawasmeh, Baraah and |
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Atou, Houdaifa and |
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Sibaee, Serry and |
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Alsayadi, Hamzah A. and |
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Al-Dhabyani, Walid and |
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Al-shaibani, Maged S. and |
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El aatar, Aya and |
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Qandos, Nour and |
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Alhamouri, Rahaf and |
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Ahmad, Samar and |
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AL-Ghrawi, Mohammed Anwar and |
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Yacoub, Aminetou and |
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AbuHweidi, Ruwa and |
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Lemin, Vatimetou Mohamed and |
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Abdel-Salam, Reem and |
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Bashiti, Ahlam and |
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Ammar, Adel and |
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Alansari, Aisha and |
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Ashraf, Ahmed and |
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Alturayeif, Nora and |
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Alcoba Inciarte, Alcides and |
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Elmadany, AbdelRahim A. and |
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Tourad, Mohamedou Cheikh and |
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Berrada, Ismail and |
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Jarrar, Mustafa and |
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Shehata, Shady and |
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Abdul-Mageed, Muhammad", |
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editor = "Christodoulopoulos, Christos and |
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Chakraborty, Tanmoy and |
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Rose, Carolyn and |
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Peng, Violet", |
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025", |
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month = nov, |
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year = "2025", |
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address = "Suzhou, China", |
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publisher = "Association for Computational Linguistics", |
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url = "[https://aclanthology.org/2025.findings-emnlp.1254/](https://aclanthology.org/2025.findings-emnlp.1254/)", |
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pages = "23048--23079", |
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ISBN = "979-8-89176-335-7" |
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} |
