ReINTEL Challenge 2020: A Comparative Study of Hybrid Deep Neural Network for Reliable Intelligence Identification on Vietnamese SNSs

09/27/2021
by   Hoang Viet Trinh, et al.
0

The overwhelming abundance of data has created a misinformation crisis. Unverified sensationalism that is designed to grab the readers' short attention span, when crafted with malice, has caused irreparable damage to our society's structure. As a result, determining the reliability of an article has become a crucial task. After various ablation studies, we propose a multi-input model that can effectively leverage both tabular metadata and post content for the task. Applying state-of-the-art finetuning techniques for the pretrained component and training strategies for our complete model, we have achieved a 0.9462 ROC-score on the VLSP private test set.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/29/2021

NLPBK at VLSP-2020 shared task: Compose transformer pretrained models for Reliable Intelligence Identification on Social network

This paper describes our method for tuning a transformer-based pretraine...
research
12/10/2020

Leveraging Transfer Learning for Reliable Intelligence Identification on Vietnamese SNSs (ReINTEL)

This paper proposed several transformer-based approaches for Reliable In...
research
04/15/2022

ML_LTU at SemEval-2022 Task 4: T5 Towards Identifying Patronizing and Condescending Language

This paper describes the system used by the Machine Learning Group of LT...
research
10/31/2018

Multi-Task Learning for Left Atrial Segmentation on GE-MRI

Segmentation of the left atrium (LA) is crucial for assessing its anatom...
research
02/25/2019

BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers

This paper describes our system submitted to SemEval 2019 Task 7: Rumour...
research
06/22/2022

UniCon+: ICTCAS-UCAS Submission to the AVA-ActiveSpeaker Task at ActivityNet Challenge 2022

This report presents a brief description of our winning solution to the ...

Please sign up or login with your details

Forgot password? Click here to reset