ArGAN: Arabic Gender, Ability, and Nationality Dataset for Evaluating Biases in Large Language Models (2025 · 1 citation)
Bias research on Arabic lags far behind English, partly because Arabic is heavily gendered, dialect-rich and low-resource.
NUR at IslamicEval 2025 Shared Task: Retrieval-Augmented LLMs for Qur'an and Hadith QA (2025 · 1 citation)
The paper describes the NUR team's entry for subtask 2 of IslamicEval 2025. The task is to take a Modern Standard Arabic question and return a ranked list of up to 20 Qur'anic passages or Hadiths that may answer it. Systems must also detect when no answer exists. The search space has two parts: the Thematic Qur'anic…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

MBZUAI at AMIYA Shared Task 2026: Adapting Open-Source LLMs for Dialectal Arabic ↗Proceedings of the 13th Workshop on NLP for Similar Languages, Varieties and Dialects · no summary yetRana Gaber et al.2026 · 2 citations
ArGAN: Arabic Gender, Ability, and Nationality Dataset for Evaluating Biases in Large Language ModelsWorkshop on Gender Bias in Natural Language ProcessingRanwa Aly, Yara Allam, Rana Gaber, et al.2025 · 1 citation
NUR at IslamicEval 2025 Shared Task: Retrieval-Augmented LLMs for Qur'an and Hadith QAArabic Natural Language Processing Conference (ArabicNLP)Serag Amin, Ranwa Aly, Yara Allam, et al.2025 · 1 citation

Co-authors here

5 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 4 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated 1 November 2026