QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation

• URL: http://arxiv.org/abs/2506.02295v1
• Date: Mon, 02 Jun 2025 22:21:06 GMT
• Title: QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation
• Authors: Ahmed Wasfy, Omer Nacar, Abdelakreem Elkhateb, Mahmoud Reda, Omar Elshehy, Adel Ammar, Wadii Boulila,
• Abstract summary: We present Qari-OCR, a vision-language models progressively optimized for Arabic.<n>Qari-OCR establishes a new open-source state-of-the-art with a Word Error Rate (WER) of 0.160, Character Error Rate (CER) of 0.061, and BLEU score of 0.737 on diacritically-rich texts.
• Score: 0.8944616102795021
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The inherent complexities of Arabic script; its cursive nature, diacritical marks (tashkeel), and varied typography, pose persistent challenges for Optical Character Recognition (OCR). We present Qari-OCR, a series of vision-language models derived from Qwen2-VL-2B-Instruct, progressively optimized for Arabic through iterative fine-tuning on specialized synthetic datasets. Our leading model, QARI v0.2, establishes a new open-source state-of-the-art with a Word Error Rate (WER) of 0.160, Character Error Rate (CER) of 0.061, and BLEU score of 0.737 on diacritically-rich texts. Qari-OCR demonstrates superior handling of tashkeel, diverse fonts, and document layouts, alongside impressive performance on low-resolution images. Further explorations (QARI v0.3) showcase strong potential for structural document understanding and handwritten text. This work delivers a marked improvement in Arabic OCR accuracy and efficiency, with all models and datasets released to foster further research.

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