English

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

Computation and Language 2023-06-09 v1

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.

Keywords

Cite

@article{arxiv.2306.04903,
  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},
  journal= {arXiv preprint arXiv:2306.04903},
  year   = {2023}
}

Comments

COLIEE 2023