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JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021 [article]

Ha-Thanh Nguyen, Phuong Minh Nguyen, Thi-Hai-Yen Vuong, Quan Minh Bui, Chau Minh Nguyen, Binh Tran Dang, Vu Tran, Minh Le Nguyen, Ken Satoh
2021 arXiv   pre-print
COLIEE is an annual competition in automatic computerized legal text processing.  ...  In this article, we survey and report our methods and experimental results in using deep learning in legal document processing.  ...  INTRODUCTION COLIEE is an annual competition in automatic legal text processing. The competition uses two main types of data: case law and statute law.  ... 
arXiv:2106.13405v2 fatcat:5kplhbi3qnhyzogsmavrobsyvi

JNLP Team: Deep Learning for Legal Processing in COLIEE 2020 [article]

Ha-Thanh Nguyen, Hai-Yen Thi Vuong, Phuong Minh Nguyen, Binh Tran Dang, Quan Minh Bui, Sinh Trong Vu, Chau Minh Nguyen, Vu Tran, Ken Satoh, Minh Le Nguyen
2020 arXiv   pre-print
We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020.  ...  These systems are all characterized by being pre-trained on large amounts of data before being finetuned for the specified tasks.  ...  COLIEE tasks cover two of the most popular legal systems in the world, Case law and Civil law. COLIEE provides real data from the Canadian judicial system and the Japanese legal system.  ... 
arXiv:2011.08071v1 fatcat:e7d6vmamhjbljolmv4a3zrs5ai

Transformer-Based Approaches for Legal Text Processing

Ha-Thanh Nguyen, Minh-Phuong Nguyen, Thi-Hai-Yen Vuong, Minh-Quan Bui, Minh-Chau Nguyen, Tran-Binh Dang, Vu Tran, Le-Minh Nguyen, Ken Satoh
2022 The Review of Socionetwork Strategies  
We describe in detail the processing steps for each task such as problem formulation, data processing and augmentation, pretraining, finetuning.  ...  In this paper, we introduce our approaches using Transformer-based models for different problems of the COLIEE 2021 automatic legal text processing competition.  ...  Task 3, 4, 5 uses statute law data with challenges of retrieval, entailment, and question answering, respectively.  ... 
doi:10.1007/s12626-022-00102-2 fatcat:mii4xqiksbgtppvfeebmirk6pm

Toward Improving Attentive Neural Networks in Legal Text Processing [article]

Ha-Thanh Nguyen
2022 arXiv   pre-print
Language models tend to grow larger and larger, though, without expert knowledge, these models can still fail in domain adaptation, especially for specialized fields like law.  ...  Hence, models that work well on general documents still face challenges in dealing with legal documents. We have verified the existence of this problem with our experiments in this work.  ...  Until COLIEE 2020, there are in total of 4 tasks: • Task 1 and Task 2 are case law retrieval and entailment problems. • Task 3 and Task 4 are statute law retrieval and entailment problems.  ... 
arXiv:2203.08244v1 fatcat:54rx64cucfdw3bzeujrmx5s7z4

Pretrained Transformers for Text Ranking: BERT and Beyond

Andrew Yates, Rodrigo Nogueira, Jimmy Lin
2021 Proceedings of the 14th ACM International Conference on Web Search and Data Mining  
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in response to a query for a particular task.  ...  This survey provides an overview of text ranking with neural network architectures known as transformers, of which BERT is the best-known example.  ...  However, there remain many open research questions, and thus in addition to laying out the foundations of pretrained transformers for text ranking, this survey also attempts to prognosticate where the  ... 
doi:10.1145/3437963.3441667 fatcat:6teqmlndtrgfvk5mneq5l7ecvq