# NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Task arXiv: https://arxiv.org/abs/2103.08466 ยท HTML: https://mlsanity.com/paper/2103.08466/ ## Key facts - Cited by 32 papers in the map (data through 14 Oct 2026). - Builds on 10 of its 47 references that are in the map. - First posted on arXiv 4 Mar 2021. ## Builds on (most cited first, 10 of 10) - [Parameter-Efficient Transfer Learning for NLP](https://mlsanity.com/paper/1902.00751/) (2019) - [AraBERT: Transformer-based Model for Arabic Language Understanding](https://mlsanity.com/paper/2003.00104/) (2020) - [ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic](https://mlsanity.com/paper/2101.01785/) (2020) - [NADI 2020: The First Nuanced Arabic Dialect Identification Shared Task](https://mlsanity.com/paper/2010.11334/) (2020) - [AraELECTRA: Pre-Training Text Discriminators for Arabic Language Understanding](https://mlsanity.com/paper/2012.15516/) (2020) - [Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identification](https://mlsanity.com/paper/1808.07674/) (2018) - [A Large Scale Corpus of Gulf Arabic](https://mlsanity.com/paper/1609.02960/) (2016) - [Automatic Arabic Dialect Identification Systems for Written Texts: A Survey](https://mlsanity.com/paper/2009.12622/) (2020) - [Adapting MARBERT for Improved Arabic Dialect Identification: Submission to the NADI 2021 Shared Task](https://mlsanity.com/paper/2103.01065/) (2021) - [Dialect Identification in Nuanced Arabic Tweets Using Farasa Segmentation and AraBERT](https://mlsanity.com/paper/2102.09749/) (2021) ## Built on by (most cited first, 30 of 32) - [Natural Language Processing for Dialects of a Language: A Survey](https://mlsanity.com/paper/2401.05632/) (2024) - [NADI 2023: The Fourth Nuanced Arabic Dialect Identification Shared Task](https://mlsanity.com/paper/2310.16117/) (2023) - [ALDi: Quantifying the Arabic Level of Dialectness of Text](https://mlsanity.com/paper/2310.13747/) (2023) - [NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task](https://mlsanity.com/paper/2210.09582/) (2022) - [NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task](https://mlsanity.com/paper/2407.04910/) (2024) - [Arabic Dialect Identification under Scrutiny: Limitations of Single-label Classification](https://mlsanity.com/paper/2310.13661/) (2023) - [JASMINE: Arabic GPT Models for Few-Shot Learning](https://mlsanity.com/paper/2212.10755/) (2022) - [Nabra: Syrian Arabic Dialects with Morphological Annotations](https://mlsanity.com/paper/2310.17315/) (2023) - [Camelira: An Arabic Multi-Dialect Morphological Disambiguator](https://mlsanity.com/paper/2211.16807/) (2022) - [Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks](https://mlsanity.com/paper/2411.01192/) (2024) - [Lisan: Yemeni, Iraqi, Libyan, and Sudanese Arabic Dialect Copora with Morphological Annotations](https://mlsanity.com/paper/2212.06468/) (2022) - [BERT-based Multi-Task Model for Country and Province Level Modern Standard Arabic and Dialectal Arabic Identification](https://mlsanity.com/paper/2106.12495/) (2021) - [Exploiting Dialect Identification in Automatic Dialectal Text Normalization](https://mlsanity.com/paper/2407.03020/) (2024) - [NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task](https://mlsanity.com/paper/2509.02038/) (2025) - [DialectalArabicMMLU: Benchmarking Dialectal Capabilities in Arabic and Multilingual Language Models](https://mlsanity.com/paper/2510.27543/) (2025) - [Similarities between Arabic Dialects: Investigating Geographical Proximity](https://mlsanity.com/paper/2105.04221/) (2021) - [Supporting Undotted Arabic with Pre-trained Language Models](https://mlsanity.com/paper/2111.09791/) (2021) - [VoxArabica: A Robust Dialect-Aware Arabic Speech Recognition System](https://mlsanity.com/paper/2310.11069/) (2023) - [USTHB at NADI 2023 shared task: Exploring Preprocessing and Feature Engineering Strategies for Arabic Dialect Identification](https://mlsanity.com/paper/2312.10536/) (2023) - [A Benchmark Study of Contrastive Learning for Arabic Social Meaning](https://mlsanity.com/paper/2210.12314/) (2022) - [Maknuune: A Large Open Palestinian Arabic Lexicon](https://mlsanity.com/paper/2210.12985/) (2022) - [Revisiting Common Assumptions about Arabic Dialects in NLP](https://mlsanity.com/paper/2505.21816/) (2025) - [sarcasm detection and quantification in arabic tweets](https://mlsanity.com/paper/2108.01425/) (2021) - [The Shared Task on Gender Rewriting](https://mlsanity.com/paper/2210.12410/) (2022) - [The Arabic Generality Score: Another Dimension of Modeling Arabic Dialectness](https://mlsanity.com/paper/2508.17347/) (2025) - [Mavericks at NADI 2023 Shared Task: Unravelling Regional Nuances through Dialect Identification using Transformer-based Approach](https://mlsanity.com/paper/2311.18739/) (2023) - [dzNLP at NADI 2024 Shared Task: Multi-Classifier Ensemble with Weighted Voting and TF-IDF Features](https://mlsanity.com/paper/2407.13608/) (2024) - [Curriculum Learning and Pseudo-Labeling Improve the Generalization of Multi-Label Arabic Dialect Identification Models](https://mlsanity.com/paper/2602.12937/) (2026) - [NLP Privacy Risk Identification in Social Media (NLP-PRISM): A Survey](https://mlsanity.com/paper/2602.15866/) (2026) - [Cultural Benchmarking of LLMs in Standard and Dialectal Arabic Dialogues](https://mlsanity.com/paper/2605.00119/) (2026) ## Abstract (arXiv) We present the findings and results of the Second Nuanced Arabic Dialect Identification Shared Task (NADI 2021). This Shared Task includes four subtasks: country-level Modern Standard Arabic (MSA) identification (Subtask 1.1), country-level dialect identification (Subtask 1.2), province-level MSA identification (Subtask 2.1), and province-level sub-dialect identification (Subtask 2.2). The shared task dataset covers a total of 100 provinces from 21 Arab countries, collected from the Twitter domain. A total of 53 teams from 23 countries registered to participate in the tasks, thus reflecting the interest of the community in this area. We received 16 submissions for Subtask 1.1 from five teams, 27 submissions for Subtask 1.2 from eight teams, 12 submissions for Subtask 2.1 from four teams, and 13 Submissions for subtask 2.2 from four teams.