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Samah Aloufi

Samah Aloufi has 4 papers in our library, in 2023–2026, most of them on Semitic languages, Language models & pretraining, Speech & spoken language; often with Nada Almarwani, Abdellah El Mekki, AbdelRahim Elmadany.

4 papers in our library · 2023–2026

OpenAlex · ORCID · h-index 7 · 19 works · 249 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 14 times in our library · ⭐ Paper Stars ranking: #9177

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

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.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset (2025 · 11 citations)
    Large vision-language models (LVLMs) tend to reflect Western viewpoints. Existing cultural VQA resources often rely on translated material, cover few images or topics, ask shallow factual questions, and treat a culture as uniform. The authors built Pearl to address these gaps. It is a large Arabic multimodal…
  2. Taibah at TAQEEM 2025: Leveraging GPT-4o for Arabic Essay Scoring (2025 · 3 citations)
    The paper describes the Taibah team's entry to the TAQEEM 2025 shared task on automated scoring of Arabic essays.
  3. SANA at NADI 2023 shared task: Ensemble of Layer-Wise BERT-based models for Dialectal Arabic Identification (2023 · 3 citations)
    The paper tackles country-level identification of Arabic dialects in tweets. This is subtask 1 (closed track) of the NADI-2023 shared task. Dialectal Arabic now dominates informal online writing, and many downstream tools need to know which variety a text uses. The authors work with the TWT-23 dataset: 18 dialect…
  4. Bulbul: A Dataset for Dialectal Arabic Speech Recognition (2026 · 1 citation)
    Arabic speech recognition struggles because speech resources are scarce and skewed toward a few varieties: MSA, Egyptian, broad Levantine, Gulf and Moroccan.

 Co-authors here

12 of 19 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 14 times (of the 149,439 papers whose bibliographies we read); 11 citing papers with a page here →.

Updated

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