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Miko Team: Deep Learning Approach for Legal Question Answering in ALQAC 2022

2022-11-04 00:50:20
Hieu Nguyen Van, Dat Nguyen, Phuong Minh Nguyen, Minh Le Nguyen
arXiv_CL
       
Abstract

We introduce efficient deep learning-based methods for legal document processing including Legal Document Retrieval and Legal Question Answering tasks in the Automated Legal Question Answering Competition (ALQAC 2022). In this competition, we achieve 1\textsuperscript{st} place in the first task and 3\textsuperscript{rd} place in the second task. Our method is based on the XLM-RoBERTa model that is pre-trained from a large amount of unlabeled corpus before fine-tuning to the specific tasks. The experimental results showed that our method works well in legal retrieval information tasks with limited labeled data. Besides, this method can be applied to other information retrieval tasks in low-resource languages.

Abstract (translated)

URL

https://arxiv.org/abs/2211.02200

PDF

https://arxiv.org/pdf/2211.02200.pdf

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