# A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment

arXiv: https://arxiv.org/abs/2502.13520 · HTML: https://mlsanity.com/paper/2502.13520/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 57 references that are in the map.
- First posted on arXiv 19 Feb 2025.

## Builds on (most cited first, 11 of 11)

- [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)
- [The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://mlsanity.com/paper/2103.06678/) (2021)
- [Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks](https://mlsanity.com/paper/1912.09393/) (2019)
- [ArabicMMLU: Assessing Massive Multitask Language Understanding in Arabic](https://mlsanity.com/paper/2402.12840/) (2024)
- [Text Readability Assessment for Second Language Learners](https://mlsanity.com/paper/1906.07580/) (2019)
- [Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features](https://mlsanity.com/paper/2109.12258/) (2021)
- [Linguistic Features for Readability Assessment](https://mlsanity.com/paper/2006.00377/) (2020)
- [Trends, Limitations and Open Challenges in Automatic Readability Assessment Research](https://mlsanity.com/paper/2105.00973/) (2021)
- [ReadMe++: Benchmarking Multilingual Language Models for Multi-Domain Readability Assessment](https://mlsanity.com/paper/2305.14463/) (2023)
- [The SAMER Arabic Text Simplification Corpus](https://mlsanity.com/paper/2404.18615/) (2024)

## Built on by (most cited first, 8 of 8)

- [ArabJobs: A Multinational Corpus of Arabic Job Ads](https://mlsanity.com/paper/2509.22589/) (2025)
- [Beyond LLM-as-a-Judge: Deterministic Metrics for Multilingual Generative Text Evaluation](https://mlsanity.com/paper/2604.05083/) (2026)
- [Arabic Sentence Segmentation Across Genres and Punctuation Conditions](https://mlsanity.com/paper/2606.08025/) (2026)
- [Lemmatization as a Classification Task: Results from Arabic across Multiple Genres](https://mlsanity.com/paper/2506.18399/) (2025)
- [!MSA at BAREC Shared Task 2025: Ensembling Arabic Transformers for Readability Assessment](https://mlsanity.com/paper/2509.10040/) (2025)
- [mucAI at BAREC Shared Task 2025: Towards Uncertainty Aware Arabic Readability Assessment](https://mlsanity.com/paper/2509.15485/) (2025)
- [Lexicon-Enriched Graph Modeling for Arabic Document Readability Prediction](https://mlsanity.com/paper/2509.22870/) (2025)
- [Can LLMs Control Readability? A Multi-Dimensional Evaluation Framework for CEFR-Controlled Arabic Generation](https://mlsanity.com/paper/2606.21981/) (2026)

## Abstract (arXiv)

This paper introduces the Balanced Arabic Readability Evaluation Corpus (BAREC), a large-scale, fine-grained dataset for Arabic readability assessment. BAREC consists of 69,441 sentences spanning 1+ million words, carefully curated to cover 19 readability levels, from kindergarten to postgraduate comprehension. The corpus balances genre diversity, topical coverage, and target audiences, offering a comprehensive resource for evaluating Arabic text complexity. The corpus was fully manually annotated by a large team of annotators. The average pairwise inter-annotator agreement, measured by Quadratic Weighted Kappa, is 81.8%, reflecting a high level of substantial agreement. Beyond presenting the corpus, we benchmark automatic readability assessment across different granularity levels, comparing a range of techniques. Our results highlight the challenges and opportunities in Arabic readability modeling, demonstrating competitive performance across various methods. To support research and education, we make BAREC openly available, along with detailed annotation guidelines and benchmark results.