activity
20172023
most citedBuilding Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Model

52 citations · 211 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CL2023★ 44 cited

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…

cs.CL2022

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…

cs.IR2022★ 44 cited

Attentive Deep Neural Networks for Legal Document Retrieval

Ha-Thanh Nguyen, Manh-Kien Phi, Xuan-Bach Ngo +3

Legal text retrieval serves as a key component in a wide range of legal text processing tasks such as legal question answering, legal case entailment, and statute law retrieval. Th…

cs.CL2022★ 17 cited

Transformer-based Approaches for Legal Text Processing

Ha-Thanh Nguyen, Minh-Phuong Nguyen, Thi-Hai-Yen Vuong +6

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

cs.SI2021★ 8 cited

Tweet Analysis for Enhancement of COVID-19 Epidemic Simulation: A Case Study in Japan

Vu Tran, Tomoko Matsui

The COVID-19 pandemic, which began in December 2019, progressed in a complicated manner and thus caused problems worldwide. Seeking clues to the reasons for the complicated progres…

cs.CL2021

HYDRA -- Hyper Dependency Representation Attentions

Ha-Thanh Nguyen, Vu Tran, Tran-Binh Dang +3

Attention is all we need as long as we have enough data. Even so, it is sometimes not easy to determine how much data is enough while the models are becoming larger and larger. In…