mlsanityData to 7 Oct 2026

A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions

arXiv 2501.13419 ↗First posted 23 Jan 2025cs.CLcited by 5

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Abstract (arXiv)

Language in the Arab world presents a complex diglossic and multilingual setting, involving the use of Modern Standard Arabic, various dialects and sub-dialects, as well as multiple European languages. This diverse linguistic landscape has given rise to code-switching, both within Arabic varieties and between Arabic and foreign languages. The widespread occurrence of code-switching across the region makes it vital to address these linguistic needs when developing language technologies. In this paper, we provide a review of the current literature in the field of code-switched Arabic NLP, offering a broad perspective on ongoing efforts, challenges, research gaps, and recommendations for future research directions.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 54 of its 203 references that are in the map. First posted on arXiv 23 Jan 2025.

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54 of 203 references.

References · 54

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38 more
  1. 2019Overview for the Second Shared Task on Language Identification in Code-Switched Datacited by 33
  2. 2023NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Taskcited by 29
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  16. 2020Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviewscited by 10
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  38. 2023Data Augmentation Techniques for Machine Translation of Code-Switched Texts: A Comparative Studycited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.