Nguyen Huu Dung
2024
Enhancing Legal Violation Identification with LLMs and Deep Learning Techniques: Achievements in the LegalLens 2024 Competition
Nguyen Tan Minh
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Duy Ngoc Mai
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Le Xuan Bach
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Nguyen Huu Dung
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Pham Cong Minh
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Ha Thanh Nguyen
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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
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Co-authors
- Nguyen Tan Minh 1
- Duy Ngoc Mai 1
- Le Xuan Bach 1
- Pham Cong Minh 1
- Ha-Thanh Nguyen 1
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