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

Vuong, Thi-Hai-Yen, Nguyen, Hai-Long, Nguyen, Tan-Minh, Nguyen, Hoang-Trung, Nguyen, Thai-Binh, Nguyen, Ha-Thanh

arXiv.org Artificial Intelligence 

This paper presents the NOWJ team's approach to the COL-IEE 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.

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