LAILA: A Large Trait-Based Dataset for Arabic Automated Essay Scoring
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Abstract (arXiv)
Automated Essay Scoring (AES) has gained increasing attention in recent years, yet research on Arabic AES remains limited due to the lack of publicly available datasets. To address this, we introduce LAILA, the largest publicly available Arabic AES dataset to date, comprising 7,859 essays annotated with holistic and trait-specific scores on seven dimensions: relevance, organization, vocabulary, style, development, mechanics, and grammar. We detail the dataset design, collection, and annotations, and provide benchmark results using state-of-the-art Arabic and English models in prompt-specific and cross-prompt settings. LAILA fills a critical need in Arabic AES research, supporting the development of robust scoring systems.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 8 of its 46 references that are in the map. First posted on arXiv 30 Dec 2025.
Builds on
8 of 46 references.
References · 8
- 2020AraBERT: Transformer-based Model for Arabic Language Understandingcited by 362
- 2025Fanar: An Arabic-Centric Multimodal Generative AI Platformcited by 67
- 2021AraT5: Text-to-Text Transformers for Arabic Language Generationcited by 63
- 2024ALLaM: Large Language Models for Arabic and Englishcited by 55
- 2023Prompt- and Trait Relation-aware Cross-prompt Essay Trait Scoringcited by 24
- 2025Command R7B Arabic: A Small, Enterprise Focused, Multilingual, and Culturally Aware Arabic LLMcited by 16
- 2025How well can LLMs Grade Essays in Arabic?cited by 6
- 2024Automated essay scoring in Arabic: a dataset and analysis of a BERT-based systemcited by 5
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Citing papers per year: 2026: 3.
3 papers.