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SAILER is a structure-aware pre-trained language model. It is highlighted in the following three aspects:

  • SAILER fully utilizes the structural information contained in legal case documents and pays more attention to key legal elements, similar to how legal experts browse legal case documents.

  • SAILER employs an asymmetric encoder-decoder architecture to integrate several different pre-training objectives. In this way, rich semantic information across tasks is encoded into dense vectors.

  • SAILER has powerful discriminative ability, even without any legal annotation data. It can distinguish legal cases with different charges accurately.

SAILER_en_finetune pre-training on English legal case documents and finetuning on the COLIEE training data

If you find our work useful, please do not save your star and cite our work:

@misc{SAILER,
      title={SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval}, 
      author={Haitao Li and Qingyao Ai and Jia Chen and Qian Dong and Yueyue Wu and Yiqun Liu and Chong Chen and Qi Tian},
      year={2023},
      eprint={2304.11370},
      archivePrefix={arXiv},
      primaryClass={cs.IR}
}
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