Nguyen Huu Dung


2024

pdf bib
Enhancing Legal Violation Identification with LLMs and Deep Learning Techniques: Achievements in the LegalLens 2024 Competition
Nguyen Tan Minh | Duy Ngoc Mai | Le Xuan Bach | Nguyen Huu Dung | Pham Cong Minh | Ha Thanh Nguyen | Thi Hai Yen Vuong
Proceedings of the Natural Legal Language Processing Workshop 2024

LegalLens is a competition organized to encourage advancements in automatically detecting legal violations. This paper presents our solutions for two tasks Legal Named Entity Recognition (L-NER) and Legal Natural Language Inference (L-NLI). Our approach involves fine-tuning BERT-based models, designing methods based on data characteristics, and a novel prompting template for data augmentation using LLMs. As a result, we secured first place in L-NER and third place in L-NLI among thirty-six participants. We also perform error analysis to provide valuable insights and pave the way for future enhancements in legal NLP. Our implementation is available at https://github.com/lxbach10012004/legal-lens/tree/main