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Hamzah A. Alsayadi

Hamzah A. Alsayadi has 3 papers in our library, in 2025–2026, most of them on Semitic languages, Language models & pretraining, Machine translation; often with Abdellah El Mekki, Omer Nacar, Samar M. Magdy.

3 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 9 · 28 works · 246 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 83 times in our library · ⭐ Paper Stars ranking: #8030

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Ibb UniversityIbb · Yemen2008–2025 · 11 papersEmployment since 2008 · Teacher Assistant, Computer Science🎓Ain Shams UniversityCairo · Egypt2017–2025 · 10 papersEducation 2017–2022 · Ph.D., Computer Science

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksEducation · 1 workSocial Sciences · 1 workInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Semitic languages · 3 worksLanguage models & pretraining · 2 worksMachine translation · 1 work

 Works by year

2020s

20261 paper20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Palm: A Culturally Inclusive and Linguistically Diverse Dataset for Arabic LLMs (2025 · 37 citations)
    Arabic LLMs often reflect Western cultural assumptions, largely because their instruction data is machine-generated or translated from English.
  2. Alexandria: A Multi-Domain Dialectal Arabic Machine Translation Dataset for Culturally Inclusive and Linguistically Diverse LLMs (2026 · 4 citations)
    In day-to-day life, Arabic speakers mostly use their local dialects instead of Modern Standard Arabic. MT systems trained mainly on MSA or English-centric data therefore handle dialectal input poorly. Earlier parallel resources (PADIC, MADAR, FLORES+) have limits: narrow domains, short sentences, or dialect entries…
  3. Hamyaria at PalmX2025: Leveraging Large Language Models to Improve Arabic Multiple-Choice Questions in Cultural and Islamic Domains (2025 · 1 citation)
    The paper reports a system for the PalmX 2025 shared task, which benchmarks how well LLMs answer Arabic multiple-choice questions about general culture and Islamic knowledge.

 Co-authors here

12 of 14 co-authors with a page, the most papers together first.

Venues

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

 Cited by

Papers of our library cite their works 83 times (of the 149,439 papers whose bibliographies we read); 57 citing papers with a page here →.

Updated

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