Legal artificial intelligence (LegalAI) aims to benefit legal systems with the technology of artificial intelligence, especially natural language processing (NLP). Recently, inspired by the success of pre-trained language models (PLMs) in the generic domain, many LegalAI researchers devote their effort to apply PLMs to legal tasks. However, utilizing PLMs to address legal tasks is still challenging, as the legal documents usually consist of thousands of tokens, which is far longer than the length that mainstream PLMs can process. In this paper, we release the Longformer-based pre-trained language model, named as Lawformer, for Chinese legal long documents understanding. We evaluate Lawformer on a variety of LegalAI tasks, including judgment prediction, similar case retrieval, legal reading comprehension, and legal question answering. The experimental results demonstrate that our model can achieve promising improvement on tasks with long documents as inputs.

本文介绍了一种基于Longformer的预训练语言模型，名为Lawformer，用于理解中国法律长文档。作者在判决预测、相似案例检索、法律阅读理解和法律问答等多个LegalAI任务上评估了模型性能，并表明该模型可以有效应用于处理长文档型法律任务。

Lawformer: 面向中文法律长文本的预训练语言模型