The purpose of this paper is to explore the application of large language models(LLMs)in legal case retrieval and to evaluate their potential for providing legal professionals with more efficient work aids.Currently,a...The purpose of this paper is to explore the application of large language models(LLMs)in legal case retrieval and to evaluate their potential for providing legal professionals with more efficient work aids.Currently,although pre-trained models have made great progress in legal case retrieval,they are often limited to specific types of law(e.g.,criminal law,civil law,etc.)and lack the ability to generalize across different types of law.Moreover,most models can only deal with a single task,whereas the legal case retrieval task requires a model to have a superb comprehension of legal texts,involving multiple subtasks and requiring multitasking capabilities.Therefore,the large language model,which has super generalization and multitasking ability,can solve the above problems.In order to explore the application of large language models for legal case retrieval in the legal domain,this paper evaluates a series of emerging large language models,including multilingual models,homegrown large models,and models specifically designed for the legal domain.These models are used to retrieve legal cases and its associated subtasks.Based on the Supreme People’s Court definition,the legal case retrieval task is broken down into seven subtasks:event detection,fact generation,trigger word extraction,keyword extraction,summarization,dispute focus identification,and reasoning generation.Using a variety of evaluation metrics,the experiments demonstrated that these emerging models have significant potential in the field of legal case retrieval,even with few shot samples.The research in this paper not only introduces new ideas in the field of legal case retrieval,but also empirically verifies the potential of LLMs to improve the quality and efficiency of retrieval.It proves the value of large language models in this field and is expected to significantly enhance the efficiency of legal practitioners,as well as promote the consistency and fairness of legal judgments through the use of emerging technologies.展开更多
基金supported by the Large-scale Industry Model Evaluation Capability Development(CXFZ2024004)the National Social Science Foundation of China(22ZD035)the Research Innovation Project Plan of China University of Political Science and Law(24KYGH021).
文摘The purpose of this paper is to explore the application of large language models(LLMs)in legal case retrieval and to evaluate their potential for providing legal professionals with more efficient work aids.Currently,although pre-trained models have made great progress in legal case retrieval,they are often limited to specific types of law(e.g.,criminal law,civil law,etc.)and lack the ability to generalize across different types of law.Moreover,most models can only deal with a single task,whereas the legal case retrieval task requires a model to have a superb comprehension of legal texts,involving multiple subtasks and requiring multitasking capabilities.Therefore,the large language model,which has super generalization and multitasking ability,can solve the above problems.In order to explore the application of large language models for legal case retrieval in the legal domain,this paper evaluates a series of emerging large language models,including multilingual models,homegrown large models,and models specifically designed for the legal domain.These models are used to retrieve legal cases and its associated subtasks.Based on the Supreme People’s Court definition,the legal case retrieval task is broken down into seven subtasks:event detection,fact generation,trigger word extraction,keyword extraction,summarization,dispute focus identification,and reasoning generation.Using a variety of evaluation metrics,the experiments demonstrated that these emerging models have significant potential in the field of legal case retrieval,even with few shot samples.The research in this paper not only introduces new ideas in the field of legal case retrieval,but also empirically verifies the potential of LLMs to improve the quality and efficiency of retrieval.It proves the value of large language models in this field and is expected to significantly enhance the efficiency of legal practitioners,as well as promote the consistency and fairness of legal judgments through the use of emerging technologies.
