NOWJ at COLIEE 2023 -- Multi-Task and Ensemble Approaches in Legal Information Processing

Thi-Hai-Yen Vuong, Hai-Long Nguyen, Tan-Minh Nguyen, Hoang-Trung Nguyen, Thai-Binh Nguyen +1 more
6/8/2023
cs.CL

No confident code implementation found for this paper.

Abstract

This paper presents the NOWJ team's approach to the COLIEE 2023 Competition, which focuses on advancing legal information processing techniques and applying them to real-world legal scenarios. Our team tackles the four tasks in the competition, which involve legal case retrieval, legal case entailment, statute law retrieval, and legal textual entailment. We employ state-of-the-art machine learning models and innovative approaches, such as BERT, Longformer, BM25-ranking algorithm, and multi-task learning models. Although our team did not achieve state-of-the-art results, our findings provide valuable insights and pave the way for future improvements in legal information processing.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{vuong2023nowj,
  title  = {NOWJ at COLIEE 2023 -- Multi-Task and Ensemble Approaches in Legal Information Processing},
  author = {Thi-Hai-Yen Vuong and Hai-Long Nguyen and Tan-Minh Nguyen and Hoang-Trung Nguyen and Thai-Binh Nguyen and Ha-Thanh Nguyen},
  year   = {2023},
  eprint = {2306.04903},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.04903v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2306.04903.svg)](https://codeofpaper.com/paper/2306.04903)

Discussion