Papers by Sohaila Eltanbouly

5 papers
MAPLE: A Meta-learning Framework for Cross-Prompt Essay Scoring (2026.findings-acl)

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Challenge: Current approaches to automate essay scoring (AES) treat each writing task as a separate task, resulting in inconsistent performance.
Approach: They propose a meta-learning framework that leverages prototypical networks to learn transferable representations across different writing prompts.
Outcome: The proposed framework outperforms baseline models on ELLIPSE and ASAP (English) and LAILA (Arabic) on three diverse datasets.
LAILA: A Large Trait-Based Dataset for Arabic Automated Essay Scoring (2026.eacl-long)

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Challenge: Existing Arabic resources are small in scale and lack trait-specific annotations.
Approach: They propose to use LAILA to build a large Arabic AES dataset with holistic and trait-specific annotations of seven writing proficiency traits.
Outcome: The LAILA dataset comprises 7,859 essays annotated with holistic and trait-specific scores on seven dimensions: relevance, organization, vocabulary, style, development, mechanics, and grammar.
Can Large Language Models Automatically Score Proficiency of Written Essays? (2024.lrec-main)

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Challenge: Automated essay scoring (AES) is one of the earliest research problems in natural language processing.
Approach: They propose to use large language models to analyze and score written essays using four different prompts.
Outcome: The proposed models show comparable performance on four different prompts and a slight advantage over the state-of-the-art models.
TRATES: Trait-Specific Rubric-Assisted Cross-Prompt Essay Scoring (2025.findings-acl)

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Challenge: Automated Essay Scoring (AES) has seen significant progress in assessing writing ability and trait scoring.
Approach: They propose a trait-specific and rubric-based cross-prompt AES framework that is generic yet specific to the underlying trait.
Outcome: The proposed framework achieves state-of-the-art across all traits on a widely-used dataset, with the generated LLM-based features being the most significant.
Qayyem: A Real-time Platform for Scoring Proficiency of Arabic Essays (2026.acl-demo)

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Challenge: Existing Arabic writing technologies primarily use a single quality score for essays, but there is limited support for Arabic AES.
Approach: They propose a Web-based platform that integrates Arabic AES workflows with a user-friendly interface.
Outcome: The proposed system integrates with existing Arabic scoring systems and provides a user-friendly interface.

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