---
title: "Who cites Jibril Frej — 243 papers of our library"
description: "243 papers of the Elamur Research library cite the works of Jibril Frej, found in their bibliographies; the most cited first."
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---
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# Who cites Jibril Frej

245 citations of their works from 243 papers of our library (of the 141,840 whose bibliographies we read) · 23 with a page here, the most cited first · [← Jibril Frej](https://md.research.elamur.ai/free/en/authors/jibril-frej/)

1. **[Transformers: State-of-the-Art Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wolf-2020-transformers-state-art-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Wolf, Lysandre Debut, Victor Sanh, et al.*2020 · 15,606 citations*
2. **[mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer](https://md.research.elamur.ai/free/en/papers/xue-2021-mt5-massively-multilingual-pre-trained/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Linting Xue, Noah Constant, Adam Roberts, et al.*2021 · 3,197 citations*
3. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,753 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
4. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations*
5. **[CamemBERT: a Tasty French Language Model](https://md.research.elamur.ai/free/en/papers/martin-2019-camembert-tasty-french-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, et al.*2019 · 1,267 citations*
6. **[IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages](https://md.research.elamur.ai/free/en/papers/kakwani-2020-indicnlpsuite-monolingual-corpora-evaluation-benchmarks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Divyanshu Kakwani, Anoop Kunchukuttan, Satish Golla, et al.*2020 · 730 citations*
7. [**ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic arXiv:2101.01785 · ACL-2021 camera ready version**Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi*2021 · 478 citations*](https://md.research.elamur.ai/free/en/papers/abdul-mageed-2021-arbert-marbert-deep-bidirectional-transformers/)
8. **[German's Next Language Model](https://md.research.elamur.ai/free/en/papers/chan-2020-german-s-next-language-model/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Branden Chan, Stefan Schweter, Timo Möller*2020 · 385 citations*
9. [**BERTje: A Dutch BERT Model arXiv:1912.09582**Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, et al.*2019 · 360 citations*](https://md.research.elamur.ai/free/en/papers/de-vries-2019-bertje-dutch-bert-model/)
10. **[BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla](https://md.research.elamur.ai/free/en/papers/bhattacharjee-2022-banglabert-language-model-pretraining-benchmarks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abhik Bhattacharjee, Tahmid Hasan, Wasi Ahmad, et al.*2022 · 296 citations*
11. **[IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/wilie-2020-indonlu-benchmark-resources-evaluating-indonesian/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Bryan Wilie, Karissa Vincentio, Genta Indra Winata, et al.*2020 · 265 citations*
12. **[HONEST: Measuring Hurtful Sentence Completion in Language Models](https://md.research.elamur.ai/free/en/papers/nozza-2021-honest-measuring-hurtful-sentence-completion/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Debora Nozza, Federico Bianchi, Dirk Hovy*2021 · 190 citations*
13. **[French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English](https://md.research.elamur.ai/free/en/papers/neveol-2022-french-crows-pairs-extending-challenge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aurélie Névéol, Yoann Dupont, Julien Bezançon, et al.*2022 · 107 citations*
14. [**FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language arXiv:2506.20920**Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.*2025 · 97 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/)
15. **[JGLUE: Japanese General Language Understanding Evaluation](https://md.research.elamur.ai/free/en/papers/kurihara-2022-jglue-japanese-general-language-understanding/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata*2022 · 90 citations*
16. **[ORCA: A Challenging Benchmark for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/elmadany-2023-orca-challenging-benchmark-arabic-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**AbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 83 citations*
17. [**JABER and SABER: Junior and Senior Arabic BERt arXiv:2112.04329**Abbas Ghaddar, Yimeng Wu, Ahmad Rashid, et al.*2021 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2021-jaber-saber-junior-senior-arabic/)
18. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding arXiv:2205.10687**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/)
19. **[Scalar Adjective Identification and Multilingual Ranking](https://md.research.elamur.ai/free/en/papers/soler-2021-scalar-adjective-identification-multilingual-ranking/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Aina Garí Soler, Marianna Apidianaki*2021 · 9 citations*
20. **[Annotating referential continuity in a school-writing corpus: first results (Annotation de la continuité référentielle dans un corpus scolaire – premiers résultats)](https://md.research.elamur.ai/free/en/papers/barletta-2024-annotation-de-la-continuite-referentielle/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Martina Barletta*2024 · 3 citations*
21. [**AlcLaM: Arabic Dialectal Language Model arXiv:2407.13097**Murtadha Ahmed, Saghir Alfasly, Bo Wen, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/ahmed-2024-alclam-arabic-dialectal-language-model/)
22. **[Is Biomedical Specialization Still Worth It? Insights from Domain-Adaptive Language Modelling with a New French Health Corpus](https://md.research.elamur.ai/free/en/papers/mannion-2026-is-biomedical-specialization-still-worth/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aidan Mannion, Cécile Macaire, Armand Violle, et al.*2026*
23. [**Annotating the French Wiktionary with supersenses for large scale lexical analysis: a use case to assess form-meaning relationships within the nominal lexicon COLING 2025 (Abu Dhabi)**Nicolas Angleraud, Lucie Barque, Marie Candito*2025*](https://md.research.elamur.ai/free/en/papers/angleraud-2025-french-wiktionary-supersenses/)

220 more citing papers of our library have no page here yet.

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