Papers by Kareem Mohamed Darwish

2 papers
From RAG to Agentic RAG for Faithful Islamic Question Answering (2026.findings-acl)

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Challenge: Large Language Models (LLMs) are increasingly used for Islamic question answering, where ungrounded responses may carry serious religious consequences.
Approach: They propose a bilingual, bilingual, Arabic/English benchmark with atomic single-gold answers that measures hallucination and abstention.
Outcome: The proposed model improves accuracy and robustness even with a small model.
Fanar-Sadiq: A Multi-Agent Architecture for Grounded Islamic QA (2026.acl-industry)

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Challenge: Large language models (LLMs) can answer religious knowledge queries fluently, but they often hallucinate and misattribute sources.
Approach: They propose a bilingual Arabic-English Islamic QA system that uses a multi-agent, tool-augmented architecture to route Islamic queries to specialized modules.
Outcome: The proposed system is based on a multi-agent, tool-augmented architecture and has received over 1.9M accesses in less than a year.

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