Abstract: The automatic generation of judicial documents is one of the key tasks in the construction of smart courts,aiming to enhance judicial efficiency and document quality.However,due to the blind spots of large models in judicial cognition,they struggle to understand the trial mechanism and document norms,resulting in deficiencies in the logical consistency and structural rationality of the generated documents.To address these issues,this paper proposes a method for generating judicial documents based on trial logic,which utilizes large language models to simulate the trial reasoning process and generate documents in stages.Firstly,legal elements are used to fill in the preset template to describe the “basic case facts”.Secondly,the facts and evidence are analyzed and aligned to obtain the “trial facts”.Finally,relevant legal provisions are retrieved from the knowledge base to gene-rate the “court judgment”,and the complete document is assembled.Experimental results show that,compared with the baseline model on real case file data,the proposed method has improved the F1 values of ROUGE-1,ROUGE-2,and ROUGE-L by 6.03,6.56,and 7.98 percentage points respectively,verifying the effectiveness of the proposed method.

Key words: Large language model, Judgment document generation, Knowledge base, Trial logic, Smart court