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Legal case retrieval techniques play an essential role in modern intelligentlegal systems. As an annually well-known international competition, COLIEE isaiming to achieve the state-of-the-art retrieval model for legal texts. Thispaper summarizes the approach of the championship team THUIR in COLIEE 2023. Tobe specific, we design structure-aware pre-trained language models to enhancethe understanding of legal cases. Furthermore, we propose heuristicpre-processing and post-processing approaches to reduce the influence ofirrelevant messages. In the end, learning-to-rank methods are employed to mergefeatures with different dimensions. Experimental results demonstrate thesuperiority of our proposal. Official results show that our run has the bestperformance among all submissions. The implementation of our method can befound at https://github.com/CSHaitao/THUIR-COLIEE2023.

THUIR@COLIEE 2023: Incorporating Structural Knowledge into Pre-trained Language Models for Legal Case Retrieval