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Mohamed Elaraby

Mohamed Elaraby has 4 papers in our library, in 2018–2023, most of them on Semitic languages, Language models & pretraining; often with Muhammad Abdul-Mageed, Hassan Alhuzali, Yu Wang.

4 papers in our library · 2018–2023

OpenAlex · ORCID · h-index 10 · 24 works · 264 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 143 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #5268

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

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. You Tweet What You Speak: A City-Level Dataset of Arabic Dialects (2018 · 112 citations)
    Arabic is a family of varieties, and most of its dialects have little or no data that computational models can use.
  2. Deep Models for Arabic Dialect Identification on Benchmarked Data (2018 · 85 citations)
    The authors look at automatic identification of Arabic varieties in user comments. Their starting point is the Arabic Online Commentary (AOC) corpus, a large collection of comments from news sites in which a crowd-labeled portion carries one of four tags: MSA, Egyptian (EGY), Gulf (GLF) or Levantine (LEV). Earlier…
  3. Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models (2023 · 43 citations)
    Smaller open-source LLMs invent facts far more often than models above 100B parameters, yet most hallucination research targets the large ones.
  4. A Character Level Convolutional BiLSTM for Arabic Dialect Identification (2019 · 14 citations)
    The paper addresses fine-grained Arabic dialect identification at the level of Twitter users. Each user must be assigned one of 21 countries, which is harder than separating a few broad dialect groups because neighbouring dialects look very similar in writing. The CU-RAISA team built this system for MADAR shared task…

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language ModelsarXiv:2308.11764Mohamed Elaraby, Mengyin Lu, Jacob Dunn, et al.2023 · 43 citations
  2. Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Reranking ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetMohamed Elaraby, Yang Zhong, Diane Litman2023 · 27 citations
  3. ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining ↗Proceedings of the 29th International Conference on Computational Linguistics · no summary yetMohamed Elaraby, Diane Litman2022 · 23 citations

 Co-authors here

4 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 143 times (of the 149,439 papers whose bibliographies we read); 68 citing papers with a page here →.

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