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<p>The rise of large language models (LLMs) such as ChatGPT and GPT-4 developed by OpenAI have generated significant interest in the legal domain due to their sophisticated language processing capabilities. In particular, regions like China are vigorously developing legal-specific LLMs for legal purposes. Fine-tuned with fewer parameters and based on judicial documents and Chinese case data sets, these specialized LLMs are widely expected to meet practical needs in the judicial field more effectively. However, the ability of these law-specific LLMs to perform legal tasks and their potential to outperform general LLMs has not yet been established. To fill in this research gap, we systematically evaluate a range of general and legal-specific LLMs on various legal tasks. The results show that GPT-4 maintains superior performance on most legal tasks, although legal-specific LLMs show superior performance in specific cases. This study provides insight into the factors leading to these results, hoping to enrich the discourse on the use of LLMs in the legal field.</p>

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Specialized or general AI? a comparative evaluation of LLMs’ performance in legal tasks

  • 期刊论文

  • 发表日期：

    2025年5月14日

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  • Xue Guo,
  • Yuting Huang,
  • Bin Wei,
  • Kun Kuang,
  • Yiquan Wu,
  • Leilei Gan,
  • Xianshan Huang,
  • Xianglin Dong

摘要

The rise of large language models (LLMs) such as ChatGPT and GPT-4 developed by OpenAI have generated significant interest in the legal domain due to their sophisticated language processing capabilities. In particular, regions like China are vigorously developing legal-specific LLMs for legal purposes. Fine-tuned with fewer parameters and based on judicial documents and Chinese case data sets, these specialized LLMs are widely expected to meet practical needs in the judicial field more effectively. However, the ability of these law-specific LLMs to perform legal tasks and their potential to outperform general LLMs has not yet been established. To fill in this research gap, we systematically evaluate a range of general and legal-specific LLMs on various legal tasks. The results show that GPT-4 maintains superior performance on most legal tasks, although legal-specific LLMs show superior performance in specific cases. This study provides insight into the factors leading to these results, hoping to enrich the discourse on the use of LLMs in the legal field.