THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case
  Entailment
Haitao Li Changyue Wang Weihang Su Yueyue Wu Qingyao Ai Yiqun Liu
This paper describes the approach of the THUIR team at the COLIEE 2023 Legal
Case Entailment task. This task requires the participant to identify a specific
paragraph from a given supporting case that entails the decision for the query
case. We try traditional lexical matching methods and pre-trained language
models with different sizes. Furthermore, learning-to-rank methods are employed
to further improve performance. However, learning-to-rank is not very robust on
this task. which suggests that answer passages cannot simply be determined with
information retrieval techniques. Experimental results show that more
parameters and legal knowledge contribute to the legal case entailment task.
Finally, we get the third place in COLIEE 2023. The implementation of our
method can be found at https://github.com/CSHaitao/THUIR-COLIEE2023.