The Integration of Large-Scale Language Models Into Intelligent Adjudication: Justification Rules and Implementation Pathways

Wenjian Sun; Weixiang Wan; Linying Pan; Jingyu Xu; Qiang Zeng

doi:10.5281/zenodo.10607564

Authors

Wenjian Sun Yantai University
Weixiang Wan University of Electronic Science and Technology of China
Linying Pan Trine University
Jingyu Xu Northern Arizona University
Qiang Zeng Zhejiang University

DOI:

https://doi.org/10.5281/zenodo.10607564

References:

30

Keywords:

Large Language Model, Intelligent Trial, Intelligent Demonstration, Safety Detection

Abstract

At the end of November 2022, after OpenAI released a new generation of generative artificial intelligence (AIGC) chat tool ChatGPT, it triggered a global network carnival, and articles came to it in terms of questions, conversations, interviews, and reviews. In addition to the noise and uproar, scholars from all walks of life also carried out rational reflection, and the topics of discussion mainly focused on the impact and impact on education, economy, news media, academic research and intellectual property rights and other fields, as well as the exploration of underlying logic issues such as key technologies, operation modes and application scenarios. In essence, large language model (LMMs) is the core framework of a new type of artificial intelligence such as ChatGPT, but the strength of its capability is not only related to corpus, algorithm and computing power, but also closely related to national sovereignty and many security issues, and the biggest obstacle in the realization of artificial intelligence trial is how to realize the legal argument. Therefore, it is necessary to build a set of intelligent trial argumentation rules, and build an algorithm model based on a large language model, to independently complete the trial of the case and output the judgment results for judges' reference, and explore its realization path and apply it to trial practice.

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Author Biographies

Wenjian Sun, Yantai University

Postgraduate, Electronic and information engineering, Yantai University, ShanDong.

Weixiang Wan, University of Electronic Science and Technology of China

Postgraduate, Electronics & Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Linying Pan, Trine University

Postgraduate, Information studies, Trine University, Phoenix, Arizona, USA.

Jingyu Xu, Northern Arizona University

Postgraduate, Computer Information Technology, Northern Arizona University, Flagstaff, Arizona, USA.

Qiang Zeng, Zhejiang University

Postgraduate, Computer Technology, Zhejiang University, Hangzhou, Zhejiang, China.

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