activity
20172021
most citedAn Empirical Study of Using Pre-trained BERT Models for Vietnamese Relation Extraction Task at VLSP 2020

3 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL2021

Multimodal Fusion with BERT and Attention Mechanism for Fake News Detection

Nguyen Manh Duc Tuan, Pham Quang Nhat Minh

Fake news detection is an important task for increasing the credibility of information on the media since fake news is constantly spreading on social media every day and it is a ve…

cs.CL2021★ 3 cited

An Empirical Study of Using Pre-trained BERT Models for Vietnamese Relation Extraction Task at VLSP 2020

Pham Quang Nhat Minh

In this paper, we present an empirical study of using pre-trained BERT models for the relation extraction task at the VLSP 2020 Evaluation Campaign. We applied two state-of-the-art…

cs.CL2020★ 1 cited

ReINTEL Challenge 2020: A Multimodal Ensemble Model for Detecting Unreliable Information on Vietnamese SNS

Nguyen Manh Duc Tuan, Pham Quang Nhat Minh

In this paper, we present our methods for unrealiable information identification task at VLSP 2020 ReINTEL Challenge. The task is to classify a piece of information into reliable o…

cs.CL2020★ 1 cited

Weakly-Supervised Neural Response Selection from an Ensemble of Task-Specialised Dialogue Agents

Asir Saeed, Khai Mai, Pham Minh +2

Dialogue engines that incorporate different types of agents to converse with humans are popular. However, conversations are dynamic in the sense that a selected response will chang…

cs.CL2018

A Feature-Based Model for Nested Named-Entity Recognition at VLSP-2018 NER Evaluation Campaign

Pham Quang Nhat Minh

In this report, we describe our participant named-entity recognition system at VLSP 2018 evaluation campaign. We formalized the task as a sequence labeling problem using BIO encodi…

cs.CL2018

A Feature-Rich Vietnamese Named-Entity Recognition Model

Pham Quang Nhat Minh

In this paper, we present a feature-based named-entity recognition (NER) model that achieves the start-of-the-art accuracy for Vietnamese language. We combine word, word-shape feat…