LegalRAG: A Hybrid RAG System for Multilingual Legal Information Retrieval

• URL: http://arxiv.org/abs/2504.16121v1
• Date: Sat, 19 Apr 2025 06:09:54 GMT
• Title: LegalRAG: A Hybrid RAG System for Multilingual Legal Information Retrieval
• Authors: Muhammad Rafsan Kabir, Rafeed Mohammad Sultan, Fuad Rahman, Mohammad Ruhul Amin, Sifat Momen, Nabeel Mohammed, Shafin Rahman,
• Abstract summary: We develop an efficient bilingual question-answering framework for regulatory documents, specifically the Bangladesh Police Gazettes.<n>Our approach employs modern Retrieval Augmented Generation (RAG) pipelines to enhance information retrieval and response generation.<n>This system enables efficient searching for specific government legal notices, making legal information more accessible.
• Score: 7.059964549363294
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Natural Language Processing (NLP) and computational linguistic techniques are increasingly being applied across various domains, yet their use in legal and regulatory tasks remains limited. To address this gap, we develop an efficient bilingual question-answering framework for regulatory documents, specifically the Bangladesh Police Gazettes, which contain both English and Bangla text. Our approach employs modern Retrieval Augmented Generation (RAG) pipelines to enhance information retrieval and response generation. In addition to conventional RAG pipelines, we propose an advanced RAG-based approach that improves retrieval performance, leading to more precise answers. This system enables efficient searching for specific government legal notices, making legal information more accessible. We evaluate both our proposed and conventional RAG systems on a diverse test set on Bangladesh Police Gazettes, demonstrating that our approach consistently outperforms existing methods across all evaluation metrics.

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