Papers with Arabic NLP
GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP (2023.emnlp-main)
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| Challenge: | Our study examines ChatGPT’s performance on Arabic languages and dialectal varieties. |
| Approach: | They conduct a large-scale automated and human evaluation of ChatGPT, encompassing 44 distinct language understanding and generation tasks on over 60 different datasets. |
| Outcome: | The proposed model outperforms smaller models on Arabic dialects compared to GPT-4's Modern Standard Arabic and Dialectal Arabic (DA) |
LAraBench: Benchmarking Arabic AI with Large Language Models (2024.eacl-long)
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Ahmed Abdelali, Hamdy Mubarak, Shammur Chowdhury, Maram Hasanain, Basel Mousi, Sabri Boughorbel, Samir Abdaljalil, Yassine El Kheir, Daniel Izham, Fahim Dalvi, Majd Hawasly, Nizi Nazar, Youssef Elshahawy, Ahmed Ali, Nadir Durrani, Natasa Milic-Frayling, Firoj Alam
| Challenge: | Recent advances in Large Language Models (LLMs) have significantly influenced the landscape of language and speech research. |
| Approach: | They used GPT-3.5-turbo, GPT-4, BLOOMZ, Jais-13b-chat, Whisper, and USM to tackle 33 distinct tasks across 61 datasets. |
| Outcome: | The proposed model outperforms SOTA models in zero-shot learning, with a few exceptions. |
The Bahrain Corpus: A Multi-genre Corpus of Bahraini Arabic (2022.lrec-1)
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| Challenge: | Various corpora of various sizes and representing different genres, have been created for various Arabic dialects. |
| Approach: | They propose to create a specialized corpus of Bahraini Arabic dialect, which includes written texts as well as transcripts of audio files. |
| Outcome: | The proposed corpus includes 620K words representing the Bahraini Arabic dialect . the annotated corpus is available to support researchers interested in Arabic NLP . |
Camel Treebank: An Open Multi-genre Arabic Dependency Treebank (2022.lrec-1)
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| Challenge: | CAMELTB is an open-source dependency treebank of Arabic with 13 sub-corpora . texts are publicly available (out of copyright, creative commons, or under open licenses) |
| Approach: | They present the Camel Treebank, a 188K word open-source dependency treebank of Arabic. |
| Outcome: | The CAMELTB is a 188K word open-source dependency treebank of Arabic . the texts are publicly available (out of copyright, creative commons, or under open licenses) |
A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions (2025.coling-main)
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| Challenge: | Code-switching (CSW) is a common linguistic phenomenon in multilingual societies . current literature on CSW in the arab world is limited to the Arabic language . |
| Approach: | They present a review of the literature in the field of code-switched Arabic NLP . they propose recommendations for future research . |
| Outcome: | This review provides a broad perspective on the current literature in the field of code-switched Arabic NLP . it also provides recommendations for future research . |
An Empirical Study of Pre-trained Transformers for Arabic Information Extraction (2020.emnlp-main)
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| Challenge: | Multilingual pre-trained Transformers have been shown to enable effective cross-lingual zero-shot transfer, but their performance on Arabic information extraction tasks is not well studied. |
| Approach: | They pre-train a bilingual BERT that is designed specifically for Arabic NLP and English-to-Arabic zero-shot transfer learning. |
| Outcome: | The pre-trained model significantly outperforms mBERT, XLM-RoBERTa, and AraBERT in both the supervised and zero-shot transfer settings. |
NileChat: Towards Linguistically Diverse and Culturally Aware LLMs for Local Communities (2025.emnlp-main)
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| Challenge: | Current research directions rely on synthetic data generated by translating English corpora, which often fails to represent the cultural heritage and values of local communities. |
| Approach: | They propose a method to create and retrieve pre-training data tailored to a specific community . they use Egyptian and Moroccan dialects as testbeds to test their understanding . |
| Outcome: | The proposed method outperforms existing Arabic-aware LLMs and performs on par with larger models. |
ALDi: Quantifying the Arabic Level of Dialectness of Text (2023.emnlp-main)
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| Challenge: | Existing work on Dialect Identification (DI) on the sentence level has focused on binary tasks, whereas ALDi treats the task as binary. |
| Approach: | They propose a dataset which contains 127,835 sentences manually labeled with their level of dialectness. |
| Outcome: | The proposed model can identify dialectness on a range of other corpora, providing a more nuanced picture than traditional DI systems. |
MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs (2025.findings-emnlp)
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| Challenge: | Metadata extraction relies heavily on manual annotation of documents. |
| Approach: | They propose a framework that leverages Large Language Models to automatically extract metadata attributes from scientific papers covering datasets of languages other than Arabic. |
| Outcome: | The proposed framework automates the extraction of metadata attributes from Arabic scientific papers using large language models. |