Papers by Mohamed Yahya
Palm: A Culturally Inclusive and Linguistically Diverse Dataset for Arabic LLMs (2025.acl-long)
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Fakhraddin Alwajih, Abdellah El Mekki, Samar Mohamed Magdy, AbdelRahim A. Elmadany, Omer Nacar, El Moatez Billah Nagoudi, Reem Abdel-Salam, Hanin Atwany, Youssef Nafea, Abdulfattah Mohammed Yahya, Rahaf Alhamouri, Hamzah A. Alsayadi, Hiba Zayed, Sara Shatnawi, Serry Sibaee, Yasir Ech-chammakhy, Walid Al-Dhabyani, Marwa Mohamed Ali, Imen Jarraya, Ahmed Oumar El-Shangiti, Aisha Alraeesi, Mohammed Anwar AL-Ghrawi, Abdulrahman S. Al-Batati, Elgizouli Mohamed, Noha Taha Elgindi, Muhammed Saeed, Houdaifa Atou, Issam Ait Yahia, Abdelhak Bouayad, Mohammed Machrouh, Amal Makouar, Dania Alkawi, Mukhtar Mohamed, Safaa Taher Abdelfadil, Amine Ziad Ounnoughene, Anfel Rouabhia, Rwaa Assi, Ahmed Sorkatti, Mohamedou Cheikh Tourad, Anis Koubaa, Ismail Berrada, Mustafa Jarrar, Shady Shehata, Muhammad Abdul-Mageed
| Challenge: | a year-long community-driven project covering all 22 Arab countries evaluates the cultural and dialectal capabilities of large language models. |
| Approach: | They propose a project to evaluate the cultural and dialectal capabilities of large language models. |
| Outcome: | The project evaluates the cultural and dialectal capabilities of several frontier LLMs. |
Structured Dialogue Refinement: Building Retrieval-Augmented Question Answering on Goal-Oriented Dialogues (2026.findings-acl)
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| Challenge: | Retrieval-Augmented Generation (RAG) is widely used for knowledgeintensive question answering (QA), but a large amount of real-world problem-solving knowledge is captured in goal-oriented dialogues. |
| Approach: | They propose a framework that adapts dialogue corpora for RAG at both retrieval and generation stages without altering the underlying pipeline. |
| Outcome: | The proposed framework improves retrieval quality and QA performance under dialogue-specific structural challenges. |
ComQA: A Community-sourced Dataset for Complex Factoid Question Answering with Paraphrase Clusters (N19-1)
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| Challenge: | ComQA dataset captures question phenomena and the diverse ways in which they are formulated. |
| Approach: | They propose a large dataset of real user questions that captures question phenomena and the diverse ways in which they are formulated. |
| Outcome: | The proposed dataset can be a driver of future research on factoid question answering (QA). |