Foundations of Domain-specific Large Language Models for Islamic Studies: A Comprehensive Review
Dublin Core
Title
Foundations of Domain-specific Large Language Models for Islamic Studies: A Comprehensive Review
Subject
bias mitigation; ethical AI; fiqh; Islamic studies; large language models; natural language processing; transformer architecture.
Description
Large language models (LLMs) have undergone rapid evolution and are highly effective in tasks such as text generation, question answering, and contextdriven analysis. However, the unique requirements of Islamic studies, where textual authenticity, diverse jurisprudential interpretations, and deep semantic nuances are critical, present challenges for general LLMs. This article reviews the evolution of neural language models by comparing the historical progression of
general LLMs with emerging Islamic-specific LLMs. We discuss the technical foundations of modern Transformer architectures and examine how recent
advancements, such as GPT-4, DeepSeek, and Mistral, have expanded LLM capabilities. The paper also highlights the limitations of standard evaluation metrics like perplexity and BLEU in capturing doctrinal, ethical, and interpretative
accuracy. To address these gaps, we propose specialized evaluation metrics to assess doctrinal correctness, internal consistency, and overall reliability. Finally, we outline a research roadmap aimed at developing robust, ethically aligned, and
jurisprudentially precise Islamic LLMs.
general LLMs with emerging Islamic-specific LLMs. We discuss the technical foundations of modern Transformer architectures and examine how recent
advancements, such as GPT-4, DeepSeek, and Mistral, have expanded LLM capabilities. The paper also highlights the limitations of standard evaluation metrics like perplexity and BLEU in capturing doctrinal, ethical, and interpretative
accuracy. To address these gaps, we propose specialized evaluation metrics to assess doctrinal correctness, internal consistency, and overall reliability. Finally, we outline a research roadmap aimed at developing robust, ethically aligned, and
jurisprudentially precise Islamic LLMs.
Creator
Mohamed Yassine El Amrani, Arshad Vakayil, Feroz Mohammed ,Faisal Al Amri
Source
DOI : https://doi.org/10.5614/itbj.ict.res.appl.2025.19.1.4
Publisher
IRCS-ITB
Date
22 October 2025
Contributor
Sri Wahyuni
Rights
ISSN: 2337-5787
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Mohamed Yassine El Amrani, Arshad Vakayil, Feroz Mohammed ,Faisal Al Amri, “Foundations of Domain-specific Large Language Models for Islamic Studies: A Comprehensive Review,” Repository Horizon University Indonesia, accessed January 11, 2026, https://repository.horizon.ac.id/items/show/9843.