Samer Rashwani
Samer Rashwani has 4 papers in our library, in 2025–2026, most of them on Reasoning, Semitic languages, Evaluation & benchmarks; often with Abdessalam Bouchekif, Heba Sbahi, Mohammed Ghaly.
OpenAlex · ORCID · h-index 2 · 13 works · 6 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 60 times in our library · ⭐ Paper Stars ranking: #7401
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 worksPolitical Science and International Relations · 3 worksSocial Sciences · 3 worksInformation Systems · 1 work
🧭 Topics 6Research subjects and languages the work is about.Reasoning · 3 worksEvaluation & benchmarks · 2 worksSemitic languages · 3 worksLegal AI · 1 workInformation retrieval & search · 1 workLanguage models & pretraining · 1 work
Works by year
2020s
Papers
- QIAS 2025: Overview of the Shared Task on Islamic Inheritance Reasoning and Knowledge Assessment (2025 · 32 citations)
QIAS 2025, a shared task at ArabicNLP 2025 (co-located with EMNLP 2025), tests how well large language models handle Islamic legal reasoning and religious knowledge. It has two multiple-choice subtasks, each stratified by difficulty. - Assessing Large Language Models on Islamic Legal Reasoning: Evidence from Inheritance Law Evaluation (2025 · 31 citations)
The paper asks how well current LLMs handle Islamic inheritance law (ʿilm al-mawārīth). The task is a demanding mix of reading the family situation, applying exclusion and fixed-share rules, and doing exact fractional arithmetic with corrections such as radd and ʿawl. The authors test seven models zero-shot with… - QIAS 2026: Overview of the Shared Task on Islamic Inheritance Reasoning (2026 · 3 citations)
QIAS 2026, a shared task at OSACT7 (co-located with LREC 2026), tests whether large language models can solve Islamic inheritance (ʿilm al-mawārīth) cases written in Arabic from start to finish. - Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith (2026)
Large language models, including Arabic-native ones, often misread Classical Arabic. The Qur'an and Hadith use archaic vocabulary, senses that drifted over centuries, and older grammar. Models trained mostly on modern web text therefore produce anachronistic or wrong interpretations. Earlier dictionary-grounded RAG…
Co-authors here
- Abdessalam Bouchekif ×3
- Heba Sbahi ×3
- Mohammed Ghaly ×3
- Shahd Gaben ×3
- Somaya Eltanbouly ×2
- Emad Mohamed
- Mutaz Al Khatib
- Wajdi Zaghouani
Venues
- Arabic Natural Language Processing Conference (ArabicNLP) ×2: ArabicNLP 2025 ×2
- Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks: Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks 2026
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