Go to ACL ARR 2025 May homepageNepKanun: A RAG-Based Nepali Legal Assistant
Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation . We introduce an AI-powered legal assistant that is tailored for Nepali legal texts and is built on a fine-tuned large language model. The technology provides precise, streamlined answers to natural language legal inquiries when integrated into a Retrieval-Augmented Generation (RAG) framework. It was trained using a custom dataset of high-quality question-answer pairs, and according to BERTScore, it obtained strong F1 scores of 0.82 (simple), 0.77 (moderate), and 0.71 (complex). Its usability is further confirmed by expert reviews. Our method shows how merging generation and retrieval can effectively democratize access to legal knowledge in Nepal by focusing on customized legal data and incorporating RAG.
Paper Type: Short
Research Area: Question Answering
Research Area Keywords: NLP Applications, Efficient/Low-Resource Methods for NL, Generation, Question Answering
Contribution Types: NLP engineering experiment, Approaches to low-resource settings, Publicly available software and/or pre-trained models
Languages Studied: English,Nepali
Submission Number: 3034
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