2023/06/08 by Thi-Hai-Yen Vuong, Vuong, Thi-Hai-Yen, Hai-Long Nguyen +9 · 2 citations
Social Sciences · #Artificial Intelligence in Law #Comparative and International Law Studies #Computation and Language (cs.CL) #FOS: Computer and information sciences #Legal Education and Practice Innovations
paper · pdf · doi:10.48550/arxiv.2306.04903
openalex publication_date 2023/06/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.