Large language models (LLMs) have transformed many fields, including natural language processing, computer vision, and reinforcement learning. These models have also made a significant impact in the field of law, where they are being increasingly utilized to automate various legal tasks, such as legal judgement prediction, legal document analysis, and legal document writing. However, the integration of LLMs into the legal field has also raised several legal problems, including privacy concerns, bias, and explainability. In this survey, we explore the integration of LLMs into the field of law. We discuss the various applications of LLMs in legal tasks, examine the legal challenges that arise from their use, and explore the data resources that can be used to specialize LLMs in the legal domain. Finally, we discuss several promising directions and conclude this paper. By doing so, we hope to provide an overview of the current state of LLMs in law and highlight the potential benefits and challenges of their integration.

翻译：[translated abstract in Chinese] 大型语言模型（LLMs）已变革众多领域，包括自然语言处理、计算机视觉和强化学习。这些模型在法律领域也产生了重大影响，正被日益广泛地用于自动化各类法律任务，如法律判决预测、法律文档分析及法律文档撰写。然而，将大型语言模型整合至法律领域也引发了若干法律问题，包括隐私关切、偏见及可解释性。在本综述中，我们探讨了大型语言模型在法律领域的整合应用，论述了其在法律任务中的多元应用场景，审视了使用这些模型所引发的法律挑战，并探索了用于在法律领域专业化训练大型语言模型的数据资源。最后，我们讨论了若干颇具前景的研究方向，并对全文进行了总结。通过以上工作，我们希望全面概述大型语言模型在法律领域的当前状况，并强调其整合应用中的潜在优势与挑战。