Abstract
This paper describes the submission of team YNU-HPCC to SemEval-2024 for Task 5: The Legal Argument Reasoning Task in Civil Procedure. The task asks candidates the topic, questions, and answers, classifying whether a given candidate’s answer is correct (True) or incorrect (False). To make a sound judgment, we propose a system. This system is based on fine-tuning the Legal-BERT model that specializes in solving legal problems. Meanwhile,Regularized Dropout (R-Drop) and focal Loss were used in the model. R-Drop is used for data augmentation, and focal loss addresses data imbalances. Our system achieved relatively good results on the competition’s official leaderboard. The code of this paper is available at https://github.com/YNU-PengShi/SemEval-2024-Task5.- Anthology ID:
- 2024.semeval-1.108
- Volume:
- Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
- Month:
- June
- Year:
- 2024
- Address:
- Mexico City, Mexico
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 757–762
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.108
- DOI:
- Cite (ACL):
- Peng Shi, Jin Wang, and Xuejie Zhang. 2024. YNU-HPCC at SemEval-2024 Task 5: Regularized Legal-BERT for Legal Argument Reasoning Task in Civil Procedure. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 757–762, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- YNU-HPCC at SemEval-2024 Task 5: Regularized Legal-BERT for Legal Argument Reasoning Task in Civil Procedure (Shi et al., SemEval 2024)
- PDF:
- https://preview.aclanthology.org/ingestion-checklist/2024.semeval-1.108.pdf