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Sultan Alrowili

Sultan Alrowili has 5 papers in our library, in 2021–2026, most of them on Semitic languages, Question answering, Language models & pretraining; often with K. Vijay-Shanker, Abdelrahim Qaddoumi, Abderrahmane Issam.

5 papers in our library · 2021–2026

OpenAlex · h-index 3 · 17 works · 83 citations OpenAlex, 2026-10-14

📄 5 works in our library · 🔗 Cited 9 times in our library · ⭐ Paper Stars ranking: #8971

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

🏢IBMArmonk · United States2026 · 4 paperscurrent🎓University of DelawareNewark · United States2021–2023 · 10 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 5 worksComputer Science · 5 worksArtificial Intelligence · 5 worksLanguage and Linguistics · 5 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Semitic languages · 5 worksLanguage models & pretraining · 1 workQuestion answering · 2 worksVision & language · 1 work

 Works by year

2020s

20261 paper20231 paper20222 papers20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. ArabicTransformer: Efficient Large Arabic Language Model with Funnel Transformer and ELECTRA Objective (2021 · 8 citations)
    Pre-training large Transformer encoders for Arabic, as done for AraBERT and AraELECTRA, is expensive. That cost puts large models out of reach for many research groups. The authors look for an architecture that grows capacity without raising pre-training cost. They combine Funnel Transformer with the ELECTRA…
  2. Generative Approach for Gender-Rewriting Task with ArabicT5 (2022 · 7 citations)
    The paper addresses Arabic gender rewriting. The task is to change a sentence so that first- and second-person references (I/you) match a requested gender combination, using the APGC corpus. The prior state of the art, the multi-step model of Alhafni et al., chains four components: gender identification, a…
  3. The Shared Task on Gender Rewriting (2022 · 3 citations)
    This paper reports on a shared task, held at WANLP 2022, on gender rewriting for Modern Standard Arabic. The task takes a sentence and produces versions that fit each combination of speaker gender and listener gender. In Arabic, words that refer to the first or second person carry grammatical gender, so a system that…
  4. ArTrivia: Harvesting Arabic Wikipedia to Build A New Arabic Question Answering Dataset (2023 · 2 citations)
    Arabic extractive QA datasets suffer from three problems: narrow topical coverage (few source articles), skewed question patterns from crowd workers (about a third of Arabic TyDi questions simply ask what or who an entity is), and small size due to crowd-sourcing costs.
  5. AraVQA: Building a New Arabic Factoid Visual Question Answering Dataset from Wikipedia (2026 · 1 citation)
    Arabic vision–language models have few resources for testing encyclopedic, fact-based knowledge. Existing Arabic VQA sets mostly cover culture or dialects, are small and hand-curated, or are not public. The authors built an automatic pipeline over the Arabic Wikipedia dump. It uses MediaWiki template tags to split…

 Co-authors here

12 of 13 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 9 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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