mlsanityData to 14 Oct 2026

Revisiting Common Assumptions about Arabic Dialects in NLP

arXiv 2505.21816 ↗First posted 27 May 2025cs.CLcited by 2

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Abstract (arXiv)

Arabic has diverse dialects, where one dialect can be substantially different from the others. In the NLP literature, some assumptions about these dialects are widely adopted (e.g., ``Arabic dialects can be grouped into distinguishable regional dialects") and are manifested in different computational tasks such as Arabic Dialect Identification (ADI). However, these assumptions are not quantitatively verified. We identify four of these assumptions and examine them by extending and analyzing a multi-label dataset, where the validity of each sentence in 11 different country-level dialects is manually assessed by speakers of these dialects. Our analysis indicates that the four assumptions oversimplify reality, and some of them are not always accurate. This in turn might be hindering further progress in different Arabic NLP tasks.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 21 of its 88 references that are in the map. First posted on arXiv 27 May 2025.

Builds on

21 of 88 references.

References · 21

  1. 2017Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American Englishcited by 71
  2. 2020We Need to Talk About Random Splitscited by 71
  3. 2020NADI 2020: The First Nuanced Arabic Dialect Identification Shared Taskcited by 47
  4. 2020Arabic Dialect Identification in the Wildcited by 45
  5. 2021NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Taskcited by 32
  6. 2023NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Taskcited by 29
  7. 2023ALDi: Quantifying the Arabic Level of Dialectness of Textcited by 24
  8. 2018Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identificationcited by 23
  9. 2022NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Taskcited by 23
  10. 2024NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Taskcited by 23
  11. 2020Multi-Dialect Arabic BERT for Country-Level Dialect Identificationcited by 15
  12. 2022Towards Responsible Natural Language Annotation for the Varieties of Arabiccited by 14
9 more
  1. 2023Arabic Dialect Identification under Scrutiny: Limitations of Single-label Classificationcited by 13
  2. 2023Language Variety Identification with True Labelscited by 12
  3. 2024AL-QASIDA: Analyzing LLM Quality and Accuracy Systematically in Dialectal Arabiccited by 11
  4. 2020Automatic Arabic Dialect Identification Systems for Written Texts: A Surveycited by 10
  5. 2021BERT-based Multi-Task Model for Country and Province Level Modern Standard Arabic and Dialectal Arabic Identificationcited by 7
  6. 2021Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Taskcited by 5
  7. 2024Estimating the Level of Dialectness Predicts Interannotator Agreement in Multi-dialect Arabic Datasetscited by 4
  8. 2024Common Ground, Diverse Roots: The Difficulty of Classifying Common Examples in Spanish Varietiescited by 3
  9. 2021TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialectcited by 1

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

2 papers.