Intelligent Legal Assistant: An Interactive Clarification System for Legal Question Answering
Rujing Yao, Yiquan Wu, Tong Zhang, Xuhui Zhang, Yuting Huang, Yang Wu,, Jiayin Yang, Changlong Sun, Fang Wang, Xiaozhong Liu

TL;DR
This paper introduces an interactive legal question-answering system that actively clarifies user needs by asking targeted questions, leading to more accurate and tailored legal advice using large language models.
Contribution
It presents a novel interactive system that improves legal question answering accuracy by engaging users in a clarification process based on their initial queries.
Findings
System effectively captures user needs through interactive clarification.
Enhanced accuracy in legal advice compared to non-interactive systems.
Provides detailed legal analysis after information collection.
Abstract
The rise of large language models has opened new avenues for users seeking legal advice. However, users often lack professional legal knowledge, which can lead to questions that omit critical information. This deficiency makes it challenging for traditional legal question-answering systems to accurately identify users' actual needs, often resulting in imprecise or generalized advice. In this work, we develop a legal question-answering system called Intelligent Legal Assistant, which interacts with users to precisely capture their needs. When a user poses a question, the system requests that the user select their geographical location to pinpoint the applicable laws. It then generates clarifying questions and options based on the key information missing from the user's initial question. This allows the user to select and provide the necessary details. Once all necessary information is…
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Taxonomy
TopicsArtificial Intelligence in Law · Legal Education and Practice Innovations
