Search Results for author: Ha-Thanh Nguyen

Found 29 papers, 1 papers with code

GPTs and Language Barrier: A Cross-Lingual Legal QA Examination

no code implementations26 Mar 2024 Ha-Thanh Nguyen, Hiroaki Yamada, Ken Satoh

In this paper, we explore the application of Generative Pre-trained Transformers (GPTs) in cross-lingual legal Question-Answering (QA) systems using the COLIEE Task 4 dataset.

Benchmarking Question Answering +1

Balancing Exploration and Exploitation in LLM using Soft RLLF for Enhanced Negation Understanding

no code implementations2 Mar 2024 Ha-Thanh Nguyen, Ken Satoh

Finetuning approaches in NLP often focus on exploitation rather than exploration, which may lead to suboptimal models.

Logical Reasoning Negation +1

A Deep Learning-Based System for Automatic Case Summarization

no code implementations13 Dec 2023 Minh Duong, Long Nguyen, Yen Vuong, Trong Le, Ha-Thanh Nguyen

This paper presents a deep learning-based system for efficient automatic case summarization.

Constructing a Knowledge Graph for Vietnamese Legal Cases with Heterogeneous Graphs

no code implementations16 Sep 2023 Thi-Hai-Yen Vuong, Minh-Quan Hoang, Tan-Minh Nguyen, Hoang-Trung Nguyen, Ha-Thanh Nguyen

This paper presents a knowledge graph construction method for legal case documents and related laws, aiming to organize legal information efficiently and enhance various downstream tasks.

graph construction

NOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models

no code implementations16 Sep 2023 Tan-Minh Nguyen, Xuan-Hoa Nguyen, Ngoc-Duy Mai, Minh-Quan Hoang, Van-Huan Nguyen, Hoang-Viet Nguyen, Ha-Thanh Nguyen, Thi-Hai-Yen Vuong

This paper describes the NOWJ1 Team's approach for the Automated Legal Question Answering Competition (ALQAC) 2023, which focuses on enhancing legal task performance by integrating classical statistical models and Pre-trained Language Models (PLMs).

Learning-To-Rank Question Answering +3

RMDM: A Multilabel Fakenews Dataset for Vietnamese Evidence Verification

no code implementations16 Sep 2023 Hai-Long Nguyen, Thi-Kieu-Trang Pham, Thai-Son Le, Tan-Minh Nguyen, Thi-Hai-Yen Vuong, Ha-Thanh Nguyen

In this study, we present a novel and challenging multilabel Vietnamese dataset (RMDM) designed to assess the performance of large language models (LLMs), in verifying electronic information related to legal contexts, focusing on fake news as potential input for electronic evidence.


Black-Box Analysis: GPTs Across Time in Legal Textual Entailment Task

no code implementations11 Sep 2023 Ha-Thanh Nguyen, Randy Goebel, Francesca Toni, Kostas Stathis, Ken Satoh

The evolution of Generative Pre-trained Transformer (GPT) models has led to significant advancements in various natural language processing applications, particularly in legal textual entailment.

Natural Language Inference

Improving Vietnamese Legal Question--Answering System based on Automatic Data Enrichment

no code implementations8 Jun 2023 Thi-Hai-Yen Vuong, Ha-Thanh Nguyen, Quang-Huy Nguyen, Le-Minh Nguyen, Xuan-Hieu Phan

Question answering (QA) in law is a challenging problem because legal documents are much more complicated than normal texts in terms of terminology, structure, and temporal and logical relationships.

Question Answering Retrieval

NOWJ at COLIEE 2023 -- Multi-Task and Ensemble Approaches in Legal Information Processing

no code implementations8 Jun 2023 Thi-Hai-Yen Vuong, Hai-Long Nguyen, Tan-Minh Nguyen, Hoang-Trung Nguyen, Thai-Binh Nguyen, Ha-Thanh Nguyen

This paper presents the NOWJ team's approach to the COLIEE 2023 Competition, which focuses on advancing legal information processing techniques and applying them to real-world legal scenarios.

Multi-Task Learning Natural Language Inference +1

LBMT team at VLSP2022-Abmusu: Hybrid method with text correlation and generative models for Vietnamese multi-document summarization

no code implementations11 Apr 2023 Tan-Minh Nguyen, Thai-Binh Nguyen, Hoang-Trung Nguyen, Hai-Long Nguyen, Tam Doan Thanh, Ha-Thanh Nguyen, Thi-Hai-Yen Vuong

Multi-document summarization is challenging because the summaries should not only describe the most important information from all documents but also provide a coherent interpretation of the documents.

Document Summarization Multi-Document Summarization

A Brief Report on LawGPT 1.0: A Virtual Legal Assistant Based on GPT-3

no code implementations11 Feb 2023 Ha-Thanh Nguyen

LawGPT 1. 0 is a virtual legal assistant built on the state-of-the-art language model GPT-3, fine-tuned for the legal domain.

Language Modelling

Attentive Deep Neural Networks for Legal Document Retrieval

no code implementations13 Dec 2022 Ha-Thanh Nguyen, Manh-Kien Phi, Xuan-Bach Ngo, Vu Tran, Le-Minh Nguyen, Minh-Phuong Tu

The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents.

Question Answering Retrieval +1

Toward Improving Attentive Neural Networks in Legal Text Processing

no code implementations15 Mar 2022 Ha-Thanh Nguyen

In this dissertation, we selectively present the main achievements in improving attentive neural networks in automatic legal document processing.

Domain Adaptation

Transformer-based Approaches for Legal Text Processing

no code implementations13 Feb 2022 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

In this paper, we introduce our approaches using Transformer-based models for different problems of the COLIEE 2021 automatic legal text processing competition.

Sublanguage: A Serious Issue Affects Pretrained Models in Legal Domain

no code implementations15 Apr 2021 Ha-Thanh Nguyen, Le-Minh Nguyen

Legal English is a sublanguage that is important for everyone but not for everyone to understand.

SCNN: Swarm Characteristic Neural Network

no code implementations8 Mar 2021 Ha-Thanh Nguyen, Le-Minh Nguyen

Deep learning is a powerful approach with good performance on many different tasks.

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