activity
20232026
most citedNOWJ1@ALQAC 2023: Enhancing Legal Task Performance with Classic Statistical Models and Pre-trained Language Models

2 citations · 4 across the 7 of their papers we have counts for

collaborators

8 papers

cs.AI2026

L-MAD: A Systematic Evaluation of Multi-Agent Debate Structures in Legal Reasoning

Tan-Minh Nguyen, Hoang-Trung Nguyen, Huu-Dong Nguyen +3

While multi-agent debate (MAD) frameworks have shown significant potential in general reasoning, their effectiveness in highly structured, knowledge-heavy legal domains remains und…

cs.CL2025

NOWJ@COLIEE 2025: A Multi-stage Framework Integrating Embedding Models and Large Language Models for Legal Retrieval and Entailment

Hoang-Trung Nguyen, Tan-Minh Nguyen, Xuan-Bach Le +5

This paper presents the methodologies and results of the NOWJ team's participation across all five tasks at the COLIEE 2025 competition, emphasizing advancements in the Legal Case…

cs.CL2025

VLQA: The First Comprehensive, Large, and High-Quality Vietnamese Dataset for Legal Question Answering

Tan-Minh Nguyen, Hoang-Trung Nguyen, Trong-Khoi Dao +3

The advent of large language models (LLMs) has led to significant achievements in various domains, including legal text processing. Leveraging LLMs for legal tasks is a natural evo…

cs.CL2024

Exploiting LLMs' Reasoning Capability to Infer Implicit Concepts in Legal Information Retrieval

Hai-Long Nguyen, Tan-Minh Nguyen, Duc-Minh Nguyen +3

Statutory law retrieval is a typical problem in legal language processing, that has various practical applications in law engineering. Modern deep learning-based retrieval methods…

cs.CL20242 cited

Enhancing Legal Document Retrieval: A Multi-Phase Approach with Large Language Models

Hai-Long Nguyen, Duc-Minh Nguyen, Tan-Minh Nguyen +3

Large language models with billions of parameters, such as GPT-3.5, GPT-4, and LLaMA, are increasingly prevalent. Numerous studies have explored effective prompting techniques to h…

cs.CL2023

RMDM: A Multilabel Fakenews Dataset for Vietnamese Evidence Verification

Hai-Long Nguyen, Thi-Kieu-Trang Pham, Thai-Son Le +3

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 i…