44 citations · 47 across the 3 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…
Encoded Summarization: Summarizing Documents into Continuous Vector Space for Legal Case Retrieval
Vu Tran, Minh Le Nguyen, Satoshi Tojo +1
We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scori…
Black-Box Analysis: GPTs Across Time in Legal Textual Entailment Task
Ha-Thanh Nguyen, Randy Goebel, Francesca Toni +2
The evolution of Generative Pre-trained Transformer (GPT) models has led to significant advancements in various natural language processing applications, particularly in legal text…