---
title: "Who cites An Empirical Study of Pre-trained — 40 citing papers"
description: "40 papers of the Elamur Research library cite «An Empirical Study of Pre-trained Transformers for Arabic Information Extraction», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/lan-2020-empirical-study-pre-trained-transformers/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lan-2020-empirical-study-pre-trained-transformers/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [An Empirical Study of Pre-trained Transformers…](https://md.research.elamur.ai/free/en/papers/lan-2020-empirical-study-pre-trained-transformers/) / cited by

# Who cites «An Empirical Study of Pre-trained Transformers for Arabic Information Extraction»

40 papers of our library cite it (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← back to «An Empirical Study of Pre-trained Transformers for Arabic Information Extraction»](https://md.research.elamur.ai/free/en/papers/lan-2020-empirical-study-pre-trained-transformers/)

1. [**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/)
2. [**The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models arXiv:2103.06678**Go Inoue, Bashar Alhafni, Nurpeiis Baimukan, et al.*2021 · 365 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2021-interplay-variant-size-task-type/)
3. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 273 citations*
4. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models arXiv:2308.16149**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 218 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/)
5. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2024-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J Ryan, Alan Ritter, et al.*2024 · 95 citations*
6. **[Arabic Fake News Detection Based on Deep Contextualized Embedding Models](https://md.research.elamur.ai/free/en/papers/nassif-2022-arabic-fake-news-detection-based/) [Neural Computing and Applications](https://md.research.elamur.ai/free/en/venues/neural-computing-and-applications/)**Ali Bou Nassif, Ashraf Elnagar, Omar Elgendy, et al.*2022 · 90 citations*
7. **[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*
8. **[Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects](https://md.research.elamur.ai/free/en/papers/inoue-2022-morphosyntactic-tagging-pre-trained-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Go Inoue, Salam Khalifa, Nizar Habash*2022 · 58 citations*
9. **[Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation](https://md.research.elamur.ai/free/en/papers/alhafni-2023-advancements-arabic-grammatical-error-detection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bashar Alhafni, Go Inoue, Christian Khairallah, et al.*2023 · 38 citations*
10. **[Arabic Image Captioning using Pre-training of Deep Bidirectional Transformers](https://md.research.elamur.ai/free/en/papers/emami-2022-arabic-image-captioning-pre-training/) [International Natural Language Generation Conference (INLG)](https://md.research.elamur.ai/free/en/venues/inlg/)**Jonathan Emami, Pierre Nugues, Ashraf Elnagar, et al.*2022 · 33 citations*
11. **[Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 27 citations*
12. **[A Survey of Large Language Models for Arabic Language and its Dialects](https://md.research.elamur.ai/free/en/papers/mashaabi-2024-survey-large-language-models-arabic/) [ACM Transactions on Asian and Low-Resource Language Information Processing](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-asian-and-low-resource-language-information-processing/)**Malak Mashaabi, Shahad Al-Khalifa, Hend Al-Khalifa*2024 · 24 citations*
13. **[AraDepSu: Detecting Depression and Suicidal Ideation in Arabic Tweets Using Transformers](https://md.research.elamur.ai/free/en/papers/hassib-2022-aradepsu-detecting-depression-suicidal-ideation/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Mariam Hassib, Nancy Hossam, Jolie Sameh, et al.*2022 · 24 citations*
14. [**ArabianGPT: Native Arabic GPT-based Large Language Model arXiv:2402.15313**Anis Koubaa, Adel Ammar, Lahouari Ghouti, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/koubaa-2024-arabiangpt-native-arabic-gpt-based/)
15. **[A Large and Diverse Arabic Corpus for Language Modeling](https://md.research.elamur.ai/free/en/papers/ali-2022-large-diverse-arabic-corpus-language/) [Procedia Computer Science](https://md.research.elamur.ai/free/en/venues/procedia-computer-science/)**Abbas Raza Ali, Muhammad Ajmal Siddiqui, Rema Algunaibet, et al.*2022 · 16 citations*
16. **[Ar-Spider: Text-to-SQL in Arabic](https://md.research.elamur.ai/free/en/papers/almohaimeed-2024-ar-spider-text-sql-arabic/) [ACM/SIGAPP Symposium on Applied Computing (SAC)](https://md.research.elamur.ai/free/en/venues/acm-sigapp-symposium-on-applied-computing-sac/)**Saleh Almohaimeed, Saad Almohaimeed, Mansour Al Ghanim, et al.*2024 · 13 citations*
17. **[Detecting Stance of Authorities towards Rumors in Arabic Tweets: A Preliminary Study](https://md.research.elamur.ai/free/en/papers/haouari-2023-detecting-stance-authorities-towards-rumors/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Fatima Haouari, Tamer Elsayed*2023 · 12 citations*
18. **[Exploring Pre-Trained Transformers and Bilingual Transfer Learning for Arabic Coreference Resolution](https://md.research.elamur.ai/free/en/papers/min-2021-exploring-pre-trained-transformers-bilingual/) [Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC)](https://md.research.elamur.ai/free/en/venues/crac/)**Bonan Min*2021 · 11 citations*
19. **[A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions](https://md.research.elamur.ai/free/en/papers/hamed-2025-survey-code-switched-arabic-nlp/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Injy Hamed, Caroline Sabty, Slim Abdennadher, et al.*2025 · 10 citations*
20. [**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/)
21. **[Challenging the Transformer-based models with a Classical Arabic dataset: Quran and Hadith](https://md.research.elamur.ai/free/en/papers/altammami-2022-challenging-transformer-based-models-classical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Shatha Altammami, Eric Atwell*2022 · 6 citations*
22. **[CLTL at ArAIEval Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models](https://md.research.elamur.ai/free/en/papers/wang-2024-cltl-araieval-shared-task-multimodal/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Yeshan Wang, Ilia Markov*2024 · 3 citations*
23. **[DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings](https://md.research.elamur.ai/free/en/papers/mageed-2021-dialex-benchmark-evaluating-multidialectal-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Muhammad Abdul-Mageed, Shady Elbassuoni, Jad Doughman, et al.*2021 · 3 citations*
24. **[Supporting Undotted Arabic with Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/rom-2021-supporting-undotted-arabic-pre-trained/) [International Conference on Natural Language and Speech Processing](https://md.research.elamur.ai/free/en/venues/icnlsp/)**Aviad Rom, Kfir Bar*2021 · 3 citations*
25. [**From FusHa to Folk: Exploring Cross-Lingual Transfer in Arabic Language Models arXiv:2602.09826**Abdulmuizz Khalak, Abderrahmane Issam, Gerasimos Spanakis*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/khalak-2026-fusha-folk-exploring-cross-lingual/)
26. [**Investigating Persuasion Techniques in Arabic: An Empirical Study Leveraging Large Language Models arXiv:2405.12884**Abdurahmman Alzahrani, Eyad Babkier, Faisal Yanbaawi, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alzahrani-2024-investigating-persuasion-techniques-arabic-empirical/)
27. **[Improving on State-of-the-Art Models for Sentiment Analysis on Saudi-English Code-Switching Text](https://md.research.elamur.ai/free/en/papers/alghamdi-2026-improving-state-art-models-sentiment/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Samaher Alghamdi, Paul Rayson, Reem Alotibi*2026*
28. **[Integrating AI into Arabic Linguistics: A Methodological Framework for Reproducible and Interpretable Research](https://md.research.elamur.ai/free/en/papers/akzam-2026-integrating-ai-arabic-linguistics-methodological/) [Al-Ta rib Jurnal Ilmiah Program Studi Pendidikan Bahasa Arab IAIN Palangka Raya](https://md.research.elamur.ai/free/en/venues/al-ta-rib-jurnal-ilmiah-program-studi-pendidikan-bahasa-arab-iain-palangka-raya/)**Ismail Akzam, Mohammad Ikhwan Bin Abdullah*2026*
29. [**Evaluating the Effectiveness of the Foundational Models for Q&A Classification in Mental Health care arXiv:2406.15966**Hassan Alhuzali, Ashwag Alasmari*2024*](https://md.research.elamur.ai/free/en/papers/alhuzali-2024-evaluating-effectiveness-foundational-models-q/)

11 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/lan-2020-empirical-study-pre-trained-transformers/) — An Empirical Study of Pre-trained Transformers for Arabic Information Extraction