3 citations · 6 across the 6 of their papers we have counts for
5 papers · 1 filter
GPTs and Language Barrier: A Cross-Lingual Legal QA Examination
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. In t…
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…
Balancing Exploration and Exploitation in LLM using Soft RLLF for Enhanced Negation Understanding
Ha-Thanh Nguyen, Ken Satoh
Finetuning approaches in NLP often focus on exploitation rather than exploration, which may lead to suboptimal models. Given the vast search space of natural language, this limited…
Enhancing Logical Reasoning in Large Language Models to Facilitate Legal Applications
Ha-Thanh Nguyen, Wachara Fungwacharakorn, Ken Satoh
Language serves as a vehicle for conveying thought, enabling communication among individuals. The ability to distinguish between diverse concepts, identify fairness and injustice,…
Law to Binary Tree -- An Formal Interpretation of Legal Natural Language
Ha-Thanh Nguyen, Vu Tran, Ngoc-Cam Le +4
Knowledge representation and reasoning in law are essential to facilitate the automation of legal analysis and decision-making tasks. In this paper, we propose a new approach based…