# Silah: Research on Large Language Models for Islamic Inheritance Law Reasoning

> A cutting-edge research project combining supervised fine-tuning, RAG, and RAG-FT technologies to use AI for solving complex reasoning problems in Islamic inheritance law.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-03T05:42:46.000Z
- 最近活动: 2026-04-03T05:47:36.492Z
- 热度: 146.9
- 关键词: 伊斯兰继承法, 大语言模型, RAG, 监督微调, 法律AI, 宗教科技
- 页面链接: https://www.zingnex.cn/en/forum/thread/silah
- Canonical: https://www.zingnex.cn/forum/thread/silah
- Markdown 来源: floors_fallback

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## 【Introduction】Silah: Cutting-edge Research on Using AI to Solve Complex Reasoning in Islamic Inheritance Law

A research project named Silah Inheritance Reasoning LLM aims to use large language models to solve complex reasoning problems in Islamic inheritance law (Faraid). Combining three technologies—supervised fine-tuning, RAG, and RAG-FT—this project opens up a new path for the intelligent processing of religious legal texts and demonstrates the potential of deep AI applications in vertical domains.

## Project Background: Complexity and Challenges of Islamic Inheritance Law

Islamic inheritance law (Al-Faraid) is one of the most precise and mathematical branches of Islamic law, involving complex distribution rules, hierarchical kinship relationships, and handling of special cases. Traditional manual calculations are prone to omissions; the increasing complexity of modern family structures and the rise in cross-border inheritance cases have put manual processing under dual challenges of efficiency and accuracy—this is the core problem the Silah project aims to address.

## Technical Architecture: A Fusion Solution of Three Technology Stacks

Silah uses a combination of three cutting-edge technologies: 1. Supervised Fine-tuning (SFT): Learning the basic rule framework of inheritance law through massive case data; 2. Retrieval-Augmented Generation (RAG): Retrieving provisions from authoritative sharia literature to solve the model hallucination problem; 3. Retrieval-Augmented Fine-Tuning (RAG-FT): Integrating retrieval capabilities into the fine-tuning process to establish an end-to-end "retrieval-reasoning-generation" capability chain and improve reasoning coherence.

## Core Capabilities: A Structured and Compliant Reasoning System

Silah's core capability is to generate structured and rule-compliant solutions, featuring traceable steps (each decision has a clear reasoning chain), verifiable rules (calculation basis can be traced back to specific sharia provisions), and explainable results (non-technical users can understand the decision logic)—reflecting the principles of transparency, interpretability, and auditability.

## Application Prospects: Social Value Across Multiple Scenarios

Silah's potential application scenarios include: for religious scholars (assisting in verifying calculations for complex cases), legal practitioners (reference for cross-border inheritance cases), ordinary Muslim families (lowering the threshold for professional consultation), and the AI research community (providing a technical paradigm for the "AI + religious law" interdisciplinary field).

## Technical Insights: A Feasible Path for Vertical Domain AI

Silah proves that for highly specialized, rule-intensive domains, a pure general large model is insufficient; the combination of "domain fine-tuning + knowledge retrieval + reasoning enhancement" is a feasible path. The exploration of RAG-FT provides new ideas for AI applications in other vertical domains—integrating retrieval capabilities deeply into training rather than as a post-hoc patch.

## Conclusion: AI as a Bridge Connecting Ancient Wisdom and Modern Life

Silah represents a microcosm of AI's deep penetration into traditional cultural fields, and its value lies in solving complex real-world problems. With technological iteration, AI is expected to play a role in more traditional knowledge domains, becoming a bridge connecting ancient wisdom and modern life.