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