# Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation

arXiv: https://arxiv.org/abs/2305.14734 · HTML: https://mlsanity.com/paper/2305.14734/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Builds on 36 of its 103 references that are in the map.
- First posted on arXiv 24 May 2023.

## Builds on (most cited first, 30 of 36)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://mlsanity.com/paper/1906.08237/) (2019)
- [AraBERT: Transformer-based Model for Arabic Language Understanding](https://mlsanity.com/paper/2003.00104/) (2020)
- [GECToR -- Grammatical Error Correction: Tag, Not Rewrite](https://mlsanity.com/paper/2005.12592/) (2020)
- [ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic](https://mlsanity.com/paper/2101.01785/) (2020)
- [The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://mlsanity.com/paper/2103.06678/) (2021)
- [A Simple Recipe for Multilingual Grammatical Error Correction](https://mlsanity.com/paper/2106.03830/) (2021)
- [Encode, Tag, Realize: High-Precision Text Editing](https://mlsanity.com/paper/1909.01187/) (2019)
- [Is ChatGPT a Highly Fluent Grammatical Error Correction System? A Comprehensive Evaluation](https://mlsanity.com/paper/2304.01746/) (2023)
- [KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media](https://mlsanity.com/paper/2007.13184/) (2020)
- [Parallel Iterative Edit Models for Local Sequence Transduction](https://mlsanity.com/paper/1910.02893/) (2019)
- [AraT5: Text-to-Text Transformers for Arabic Language Generation](https://mlsanity.com/paper/2109.12068/) (2021)
- [Felix: Flexible Text Editing Through Tagging and Insertion](https://mlsanity.com/paper/2003.10687/) (2020)
- [Seq2Edits: Sequence Transduction Using Span-level Edit Operations](https://mlsanity.com/paper/2009.11136/) (2020)
- [Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task](https://mlsanity.com/paper/1804.05940/) (2018)
- [Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data](https://mlsanity.com/paper/1903.00138/) (2019)
- [Grammatical Error Correction: A Survey of the State of the Art](https://mlsanity.com/paper/2211.05166/) (2022)
- [Pre-Training BERT on Arabic Tweets: Practical Considerations](https://mlsanity.com/paper/2102.10684/) (2021)
- [EdiT5: Semi-Autoregressive Text-Editing with T5 Warm-Start](https://mlsanity.com/paper/2205.12209/) (2022)
- [Stronger Baselines for Grammatical Error Correction Using Pretrained Encoder-Decoder Model](https://mlsanity.com/paper/2005.11849/) (2020)
- [SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser](https://mlsanity.com/paper/2210.12484/) (2022)
- [AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization](https://mlsanity.com/paper/2203.10945/) (2022)
- [Automatic Error Type Annotation for Arabic](https://mlsanity.com/paper/2109.08068/) (2021)
- [Neural Language Correction with Character-Based Attention](https://mlsanity.com/paper/1603.09727/) (2016)
- [There's No Comparison: Reference-less Evaluation Metrics in Grammatical Error Correction](https://mlsanity.com/paper/1610.02124/) (2016)
- [Compositional Sequence Labeling Models for Error Detection in Learner Writing](https://mlsanity.com/paper/1607.06153/) (2016)
- [Context is Key: Grammatical Error Detection with Contextual Word Representations](https://mlsanity.com/paper/1906.06593/) (2019)
- [Morphosyntactic Tagging with Pre-trained Language Models for Arabic and its Dialects](https://mlsanity.com/paper/2110.06852/) (2021)
- [Classifying Syntactic Errors in Learner Language](https://mlsanity.com/paper/2010.11032/) (2020)

## Built on by (most cited first, 22 of 22)

- [Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers](https://mlsanity.com/paper/2404.04925/) (2024)
- [MedArabiQ: Benchmarking Large Language Models on Arabic Medical Tasks](https://mlsanity.com/paper/2505.03427/) (2025)
- [mEdIT: Multilingual Text Editing via Instruction Tuning](https://mlsanity.com/paper/2402.16472/) (2024)
- [Beyond English: Evaluating LLMs for Arabic Grammatical Error Correction](https://mlsanity.com/paper/2312.08400/) (2023)
- [Enhancing Text Editing for Grammatical Error Correction: Arabic as a Case Study](https://mlsanity.com/paper/2503.00985/) (2025)
- [Arabic Diacritics in the Wild: Exploiting Opportunities for Improved Diacritization](https://mlsanity.com/paper/2406.05760/) (2024)
- [Exploiting Dialect Identification in Automatic Dialectal Text Normalization](https://mlsanity.com/paper/2407.03020/) (2024)
- [LLMs in Education: Novel Perspectives, Challenges, and Opportunities](https://mlsanity.com/paper/2409.11917/) (2024)
- [Opportunities and Challenges of LLMs in Education: An NLP Perspective](https://mlsanity.com/paper/2507.22753/) (2025)
- [Enhancing Arabic Automated Essay Scoring with Synthetic Data and Error Injection](https://mlsanity.com/paper/2503.17739/) (2025)
- [Gazelle: An Instruction Dataset for Arabic Writing Assistance](https://mlsanity.com/paper/2410.18163/) (2024)
- [Strategies for Arabic Readability Modeling](https://mlsanity.com/paper/2407.03032/) (2024)
- [Computational Morphology and Lexicography Modeling of Modern Standard Arabic Nominals](https://mlsanity.com/paper/2402.00385/) (2024)
- [ARWI: Arabic Write and Improve](https://mlsanity.com/paper/2504.11814/) (2025)
- [A Tale of Two Scripts: Transliteration and Post-Correction for Judeo-Arabic](https://mlsanity.com/paper/2507.04746/) (2025)
- [Arabic Sentence Segmentation Across Genres and Punctuation Conditions](https://mlsanity.com/paper/2606.08025/) (2026)
- [Zero-shot Cross-Lingual Transfer for Synthetic Data Generation in Grammatical Error Detection](https://mlsanity.com/paper/2407.11854/) (2024)
- [Enhancing Grammatical Error Detection using BERT with Cleaned Lang-8 Dataset](https://mlsanity.com/paper/2411.15523/) (2024)
- [ArbESC+: Arabic Enhanced Edit Selection System Combination for Grammatical Error Correction Resolving conflict and improving system combination in Arabic GEC](https://mlsanity.com/paper/2511.14230/) (2025)
- [Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models](https://mlsanity.com/paper/2603.16718/) (2026)
- [ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation](https://mlsanity.com/paper/2606.10765/) (2026)
- [STAGEET: Stage-wise Typed Edit Tagging for Grammatical Error Correction with Arabic as a Case Study](https://mlsanity.com/paper/2608.28614/) (2026)

## Abstract (arXiv)

Grammatical error correction (GEC) is a well-explored problem in English with many existing models and datasets. However, research on GEC in morphologically rich languages has been limited due to challenges such as data scarcity and language complexity. In this paper, we present the first results on Arabic GEC using two newly developed Transformer-based pretrained sequence-to-sequence models. We also define the task of multi-class Arabic grammatical error detection (GED) and present the first results on multi-class Arabic GED. We show that using GED information as an auxiliary input in GEC models improves GEC performance across three datasets spanning different genres. Moreover, we also investigate the use of contextual morphological preprocessing in aiding GEC systems. Our models achieve SOTA results on two Arabic GEC shared task datasets and establish a strong benchmark on a recently created dataset. We make our code, data, and pretrained models publicly available.