Boosting legal case retrieval by query content selection with large language models-Reference-Cited by-同舟云学术

Boosting legal case retrieval by query content selection with large language models

Published:2023-11-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region
language:
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Author:

Zhou Youchao¹^ORCID,Huang Heyan²^ORCID,Wu Zhijing²^ORCID

Affiliation:

1. School of Computer Science and Technology, Beijing Institute of Technology, China and Southeast Academy of Information Technology, Beijing Institute of Technology, China and Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications, China

2. School of Computer Science and Technology, Beijing Institute of Technology, China and Southeast Academy of Information Technology, Beijing Institute of Technology, China

Funder

the National Natural Science Foundation of China

the China Postdoctoral Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624918.3625328

Reference35 articles.

1. Improving BERT-based Query-by-Document Retrieval with Multi-task Optimization

2. Zhenwei An , Quzhe Huang , Cong Jiang , Yansong Feng , and Dongyan Zhao . 2022. Do Charge Prediction Models Learn Legal Theory?arXiv preprint arXiv:2210.17108 ( 2022 ). Zhenwei An, Quzhe Huang, Cong Jiang, Yansong Feng, and Dongyan Zhao. 2022. Do Charge Prediction Models Learn Legal Theory?arXiv preprint arXiv:2210.17108 (2022).

3. Peter Anderson , Xiaodong He , Chris Buehler , Damien Teney , Mark Johnson , Stephen Gould , and Lei Zhang . 2017 . Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (2017), 6077–6086. Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, and Lei Zhang. 2017. Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering. 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (2017), 6077–6086.

4. Arian Askari , Georgios Peikos , Gabriella Pasi , and Suzan Verberne . 2022. LeiBi@ COLIEE 2022 : Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval. ArXiv abs/2205.13351 ( 2022 ). Arian Askari, Georgios Peikos, Gabriella Pasi, and Suzan Verberne. 2022. LeiBi@COLIEE 2022: Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval. ArXiv abs/2205.13351 (2022).

5. Arian Askari and Suzan Verberne . 2021 . Combining Lexical and Neural Retrieval with Longformer-based Summarization for Effective Case Law Retrieval. In Biennial Conference on Design of Experimental Search & Information Retrieval Systems. Arian Askari and Suzan Verberne. 2021. Combining Lexical and Neural Retrieval with Longformer-based Summarization for Effective Case Law Retrieval. In Biennial Conference on Design of Experimental Search & Information Retrieval Systems.

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