Summary of A Rag-based Question Answering System Proposal For Understanding Islam: Mufassirqas Llm, by Ahmet Yusuf Alan et al.
A RAG-based Question Answering System Proposal for Understanding Islam: MufassirQAS LLM
by Ahmet Yusuf Alan, Enis Karaarslan, Ömer Aydin
First submitted to arxiv on: 27 Jan 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study proposes a vector database-based Retrieval Augmented Generation (RAG) approach to enhance the accuracy and transparency of Large Language Models (LLMs). Specifically, it develops a question-answering system called “MufassirQAS” that utilizes open-access books on Islam to answer religion-related questions. The system is designed to provide trustworthy answers while avoiding harmful or offensive responses. To achieve this, the system prompts are carefully crafted to prevent insidious responses and respect people’s values. Additionally, the system shares additional information such as page numbers from relevant books and referenced articles. This approach outperforms other LLMs like ChatGPT in handling sensitive questions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study is about making computer programs that can answer questions about religions. It wants to make these programs more accurate and trustworthy. One way it’s doing this is by using a special kind of database that helps the program understand what it’s saying. The program is designed to give good answers while being respectful and not offensive. It also shares extra information like where it got its answer from, so people can know if it’s a reliable source. |
Keywords
» Artificial intelligence » Question answering » Rag » Retrieval augmented generation
