# Building Domain-Specific LLMs Faithful To The Islamic Worldview: Mirage or Technical Possibility?

arXiv: https://arxiv.org/abs/2312.06652 · HTML: https://mlsanity.com/paper/2312.06652/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2023.

## Built on by (most cited first, 3 of 3)

- [Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions](https://mlsanity.com/paper/2508.08287/) (2025)
- [Investigating Retrieval-Augmented Generation in Quranic Studies: A Study of 13 Open-Source Large Language Models](https://mlsanity.com/paper/2503.16581/) (2025)
- [Benchmarking the Legal Reasoning of LLMs in Arabic Islamic Inheritance Cases](https://mlsanity.com/paper/2508.15796/) (2025)

## Abstract (arXiv)

Large Language Models (LLMs) have demonstrated remarkable performance across numerous natural language understanding use cases. However, this impressive performance comes with inherent limitations, such as the tendency to perpetuate stereotypical biases or fabricate non-existent facts. In the context of Islam and its representation, accurate and factual representation of its beliefs and teachings rooted in the Quran and Sunnah is key. This work focuses on the challenge of building domain-specific LLMs faithful to the Islamic worldview and proposes ways to build and evaluate such systems. Firstly, we define this open-ended goal as a technical problem and propose various solutions. Subsequently, we critically examine known challenges inherent to each approach and highlight evaluation methodologies that can be used to assess such systems. This work highlights the need for high-quality datasets, evaluations, and interdisciplinary work blending machine learning with Islamic scholarship.