From RAG to Agentic: Validating Islamic-Medicine Responses with LLM Agents
On the map: LLM agents and tool use → Medical and scientific domain agents
Abstract (arXiv)
Centuries-old Islamic medical texts like Avicenna's Canon of Medicine and the Prophetic Tibb-e-Nabawi encode a wealth of preventive care, nutrition, and holistic therapies, yet remain inaccessible to many and underutilized in modern AI systems. Existing language-model benchmarks focus narrowly on factual recall or user preference, leaving a gap in validating culturally grounded medical guidance at scale. We propose a unified evaluation pipeline, Tibbe-AG, that aligns 30 carefully curated Prophetic-medicine questions with human-verified remedies and compares three LLMs (LLaMA-3, Mistral-7B, Qwen2-7B) under three configurations: direct generation, retrieval-augmented generation, and a scientific self-critique filter. Each answer is then assessed by a secondary LLM serving as an agentic judge, yielding a single 3C3H quality score. Retrieval improves factual accuracy by 13%, while the agentic prompt adds another 10% improvement through deeper mechanistic insight and safety considerations. Our results demonstrate that blending classical Islamic texts with retrieval and self-evaluation enables reliable, culturally sensitive medical question-answering.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 0 of its 16 references that are in the map. First posted on arXiv 18 Jun 2025.
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Citing papers per year: 2025: 3.
3 papers.
- 2025Assessing Large Language Models on Islamic Legal Reasoning: Evidence from Inheritance Law Evaluationcited by 10
- 2025QU-NLP at QIAS 2025 Shared Task: A Two-Phase LLM Fine-Tuning and Retrieval-Augmented Generation Approach for Islamic Inheritance Reasoningcited by 4
- 2025Can LLMs Write Faithfully? An Agent-Based Evaluation of LLM-generated Islamic Contentcited by 1
- 2025Can LLMs Write Faithfully? An Agent-Based Evaluation of LLM-generated Islamic Content28 Oct 2025
- 2025Assessing Large Language Models on Islamic Legal Reasoning: Evidence from Inheritance Law Evaluation1 Sep 2025
- 2025QU-NLP at QIAS 2025 Shared Task: A Two-Phase LLM Fine-Tuning and Retrieval-Augmented Generation Approach for Islamic Inheritance Reasoning20 Aug 2025
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