ShiZhi: A Chinese Lightweight Large Language Model for Court View Generation
This addresses the challenge of court view generation in legal AI for Chinese legal professionals, representing an incremental advance by applying a domain-specific LLM to a new dataset.
The paper tackles the problem of automatically generating court views in legal case documents by introducing ShiZhi, a lightweight large language model designed for this task, achieving 70.00 ROUGE-1 and 67.85 BLEU-1 scores on generation and 86.48% accuracy on charge prediction.
Criminal Court View Generation (CVG) is a fundamental task in legal artificial intelligence, aiming to automatically generate the "Court View" section of a legal case document. Generating court views is challenging due to the diversity and complexity of case facts, and directly generating from raw facts may limit performance. In this paper, we present ShiZhi, the first large language model (LLM) specifically designed for court view generation. We construct a Chinese Court View Generation dataset, CCVG, of more than 110K cases, each containing fact descriptions paired with corresponding court views. Based on this dataset, ShiZhi achieving 70.00 ROUGE-1 and 67.85 BLEU-1 on court view generation, as well as 86.48\% accuracy with 92.75\% macro F1 on charge prediction. Experimental results demonstrate that even a small LLM can generate reasonable and legally coherent court views when trained on high-quality domain-specific data. Our model and dataset are available at \href{https://github.com/ZhitianHou/ShiZhi}{https://github.com/ZhitianHou/ShiZhi}.