  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.
