2 citations · 2 across the 7 of their papers we have counts for
7 papers
SHAMI-MT: A Syrian Arabic Dialect to Modern Standard Arabic Bidirectional Machine Translation System
Serry Sibaee, Omer Nacar, Yasser Al-Habashi +2
The rich linguistic landscape of the Arab world is characterized by a significant gap between Modern Standard Arabic (MSA), the language of formal communication, and the diverse re…
QARI-OCR: High-Fidelity Arabic Text Recognition through Multimodal Large Language Model Adaptation
Ahmed Wasfy, Omer Nacar, Abdelakreem Elkhateb +4
The inherent complexities of Arabic script; its cursive nature, diacritical marks (tashkeel), and varied typography, pose persistent challenges for Optical Character Recognition (O…
From Guidelines to Practice: A New Paradigm for Arabic Language Model Evaluation
Serry Sibaee, Omer Nacar, Adel Ammar +3
This paper addresses critical gaps in Arabic language model evaluation by establishing comprehensive theoretical guidelines and introducing a novel evaluation framework. We first a…
SARD: A Large-Scale Synthetic Arabic OCR Dataset for Book-Style Text Recognition
Omer Nacar, Yasser Al-Habashi, Serry Sibaee +2
Arabic Optical Character Recognition (OCR) is essential for converting vast amounts of Arabic print media into digital formats. However, training modern OCR models, especially powe…
GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training
Omer Nacar, Anis Koubaa, Serry Sibaee +3
Semantic textual similarity (STS) is a critical task in natural language processing (NLP), enabling applications in retrieval, clustering, and understanding semantic relationships…
Advancing Arabic Reverse Dictionary Systems: A Transformer-Based Approach with Dataset Construction Guidelines
Serry Sibaee, Samar Ahmed, Abdullah Al Harbi +4
This study addresses the critical gap in Arabic natural language processing by developing an effective Arabic Reverse Dictionary (RD) system that enables users to find words based…