Elamur Research⌕
☰
home / authors / Samer Rashwani

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.

4 papers in our library · 2025–2026

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

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. 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.
  2. 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…
  3. 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.
  4. 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

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 60 times (of the 149,439 papers whose bibliographies we read); 29 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/samer-rashwani/