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Wissam Antoun

Wissam Antoun has 3 papers in our library, in 2020–2021, most of them on Semitic languages, Language models & pretraining, Text generation; often with Fady Baly, Hazem Hajj.

3 papers in our library · 2020–2021

OpenAlex · ORCID · h-index 9 · 33 works · 959 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 858 times in our library · 8 more in our library without a page yet · ⭐ Paper Stars ranking: #1655

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. 1 more institution on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. AraBERT: Transformer-based Model for Arabic Language Understanding (2020 · 1,302 citations)
    Arabic has rich morphology, limited NLP resources and little in common with Latin-script languages. As a result, multilingual models such as Google's multilingual BERT represent it poorly. The authors address this by training a BERT model only on Arabic, called AraBERT. It uses the standard BERT-base architecture and…
  2. AraELECTRA: Pre-Training Text Discriminators for Arabic Language Understanding (2021 · 97 citations)
    Earlier Arabic pretrained encoders, including AraBERT, Arabic-BERT and ARBERT, all relied on masked language modeling.
  3. AraGPT2: Pre-Trained Transformer for Arabic Language Generation (2021 · 79 citations)
    Arabic NLP had strong pre-trained models for understanding tasks, mostly masked-LM encoders such as AraBERT, but lacked a capable generative model.

All works

11 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. AraBERT: Transformer-based Model for Arabic Language UnderstandingarXiv:2003.00104Wissam Antoun, Fady Baly, Hazem Hajj2020 · 1,302 citations
  2. hULMonA: The Universal Language Model in Arabic ↗Proceedings of the Fourth Arabic Natural Language Processing Workshop · no summary yetObeida ElJundi et al.2019 · 89 citations
  3. Multi-Task Learning using AraBert for Offensive Language Detection ↗Proceedings of the 4th Workshop on Open-Source Arabic Corpora and Processing Tools, with a Shared Task on Offensive Language Detection · no summary yetMarc Djandji et al.2020 · 42 citations
  4. Towards a Robust Detection of Language Model-Generated Text: Is ChatGPT that easy to detect? ↗Actes de CORIA-TALN 2023. Actes de la 30e Conférence sur le Traitement Automatique des Langues Naturelles (TALN), volume 1 : travaux de recherche originaux – articles longs · no summary yetWissam Antoun et al.2023 · 29 citations
  5. Empathetic BERT2BERT Conversational Model: Learning Arabic Language Generation with Little Data ↗Proceedings of the Sixth Arabic Natural Language Processing Workshop · no summary yetTarek Naous et al.2021 · 20 citations
  6. CamemBERT 2.0: A Smarter French Language Model Aged to Perfection ↗arXiv:2411.08868 · no summary yetWissam Antoun et al.2024 · 19 citations
  7. Data-Efficient French Language Modeling with CamemBERTa ↗Findings of the Association for Computational Linguistics: ACL 2023 · no summary yetWissam Antoun, Benoît Sagot, Djamé Seddah2023 · 13 citations
  8. Gaperon: A Peppered English-French Generative Language Model Suite ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetNathan Godey et al.2026 · 5 citations
  9. Language-Switching Triggers Take a Latent Detour Through Language Models ↗arXiv:2605.18646 · no summary yetFrancis Kulumba et al.2026

 Co-authors here

2 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 858 times (of the 141,840 papers whose bibliographies we read); 198 citing papers with a page here →.

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