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IslamicTurathBench: A Multi-Task, Multi-Discipline Benchmark for Evaluating Large Language Models on the Islamic Scholarly Tradition (turath)
Shahd Gaben, Heba Sbahi, Samer Rashwani +5
Large language models (LLMs) are increasingly used for question answering, education, and research, including in religious and cultural domains where answers depend on specialised…
HalluTruthQA: A Fine-Grained Benchmark for Hallucination Detection, Localization, and Explanation in Arabic Question Answering
Abdessalam Bouchekif, Mohammed-En-Nadhir Zighem, Salah Eddine Bekhouche +9
Large language models (LLMs) can generate fluent Arabic answers, yet factual errors remain difficult to detect, localize, explain, and verify. Existing hallucination benchmarks oft…
QIAS 2026: Overview of the Shared Task on Islamic Inheritance Reasoning
Abdessalam Bouchekif, Somaya Eltanbouly, Samer Rashwani +5
This paper presents a comprehensive overview of the QIAS 2026 shared task, organized as part of the OSACT7 Workshop and co-located with LREC 2026. The shared task was designed to e…
MAWARITH: A Dataset and Benchmark for Legal Inheritance Reasoning with LLMs
Abdessalam Bouchekif, Shahd Gaben, Samer Rashwani +5
Islamic inheritance law is challenging for large language models because solving inheritance cases requires complex, structured, multi-step reasoning and the correct application of…
From RAG to Agentic RAG for Faithful Islamic Question Answering
Gagan Bhatia, Hamdy Mubarak, Mustafa Jarrar +8
Large Language Models (LLMs) are increasingly used for Islamic question answering, where ungrounded responses may carry serious religious consequences. Yet standard MCQ/MRC-style e…