LawLLM: Law Large Language Model for the US Legal System.
Dong Shu|Haoran Zhao|Xukun Liu|David Demeter|Mengnan Du|Yongfeng Zhang
| Anthology ID: | DBLP:conf/cikm/ShuZLDDZ24 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 4882-4889 |
| URL: | https://doi.org/10.1145/3627673.3680020 |
| DOI: | https://doi.org/10.1145/3627673.3680020 |
| DBLP: | conf/cikm/ShuZLDDZ24 |
| BibTeX: |
@inproceedings{shu-2024-lawllm,
author = {Dong Shu and
Haoran Zhao and
Xukun Liu and
David Demeter and
Mengnan Du and
Yongfeng Zhang},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{LawLLM: Law Large Language Model for the US Legal System}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {4882--4889},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3680020},
doi = {https://doi.org/10.1145/3627673.3680020}
}