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
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@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}
}