Thien Huu Nguyen

research

∙ 11/13/2022

Textual Data Augmentation for Patient Outcomes Prediction

Deep learning models have demonstrated superior performance in various h...

Qiuhao Lu, et al. ∙

research

∙ 11/11/2022

MINION: a Large-Scale and Diverse Dataset for Multilingual Event Detection

Event Detection (ED) is the task of identifying and classifying trigger ...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 11/11/2022

MEE: A Novel Multilingual Event Extraction Dataset

Event Extraction (EE) is one of the fundamental tasks in Information Ext...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 09/11/2022

Tutorial Recommendation for Livestream Videos using Discourse-Level Consistency and Ontology-Based Filtering

Streaming videos is one of the methods for creators to share their creat...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 09/11/2022

Improving Keyphrase Extraction with Data Augmentation and Information Filtering

Keyphrase extraction is one of the essential tasks for document understa...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 04/26/2022

Symlink: A New Dataset for Scientific Symbol-Description Linking

Mathematical symbols and descriptions appear in various forms across doc...

Viet Dac Lai, et al. ∙

research

∙ 02/19/2022

Punctuation Restoration

Given the increasing number of livestreaming videos, automatic speech re...

Viet Dac Lai, et al. ∙

research

∙ 02/19/2022

MACRONYM: A Large-Scale Dataset for Multilingual and Multi-Domain Acronym Extraction

Acronym extraction is the task of identifying acronyms and their expande...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 02/16/2022

FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction

This paper presents FAMIE, a comprehensive and efficient active learning...

Minh Van Nguyen, et al. ∙

research

∙ 12/19/2021

Predicting Patient Readmission Risk from Medical Text via Knowledge Graph Enhanced Multiview Graph Convolution

Unplanned intensive care unit (ICU) readmission rate is an important met...

Qiuhao Lu, et al. ∙

research

∙ 11/01/2021

Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey

Large, pre-trained transformer-based language models such as BERT have d...

Bonan Min, et al. ∙

research

∙ 03/16/2021

Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks

Existing works on information extraction (IE) have mainly solved the fou...

Minh Van Nguyen, et al. ∙

research

∙ 01/25/2021

MadDog: A Web-based System for Acronym Identification and Disambiguation

Acronyms and abbreviations are the short-form of longer phrases and they...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 01/09/2021

Trankit: A Light-Weight Transformer-based Toolkit for Multilingual Natural Language Processing

We introduce Trankit, a light-weight Transformer-based Toolkit for multi...

Minh Nguyen, et al. ∙

research

∙ 12/22/2020

Acronym Identification and Disambiguation Shared Tasks for Scientific Document Understanding

Acronyms are the short forms of longer phrases and they are frequently u...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 11/17/2020

Structural and Functional Decomposition for Personality Image Captioning in a Communication Game

Personality image captioning (PIC) aims to describe an image with a natu...

Thu Nguyen, et al. ∙

research

∙ 10/28/2020

What Does This Acronym Mean? Introducing a New Dataset for Acronym Identification and Disambiguation

Acronyms are the short forms of phrases that facilitate conveying length...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 10/27/2020

Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks

Recent studies on event detection (ED) haveshown that the syntactic depe...

Viet Dac Lai, et al. ∙

research

∙ 10/26/2020

Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction

The goal of Event Argument Extraction (EAE) is to find the role of each ...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 10/26/2020

Improving Aspect-based Sentiment Analysis with Gated Graph Convolutional Networks and Syntax-based Regulation

Aspect-based Sentiment Analysis (ABSA) seeks to predict the sentiment po...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 10/26/2020

Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning

Targeted opinion word extraction (TOWE) is a sub-task of aspect based se...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 06/17/2020

Extensively Matching for Few-shot Learning Event Detection

Current event detection models under super-vised learning settings fail ...

Viet Dac Lai, et al. ∙

research

∙ 02/13/2020

Exploiting the Matching Information in the Support Set for Few Shot Event Classification

The existing event classification (EC) work primarily focuseson the trad...

Viet Dac Lai, et al. ∙

research

∙ 11/05/2019

Improving Slot Filling by Utilizing Contextual Information

Slot Filling is the task of extracting the semantic concept from a given...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 11/05/2019

A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency

Definition Extraction (DE) is one of the well-known topics in Informatio...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 11/04/2019

On the Effectiveness of the Pooling Methods for Biomedical Relation Extraction with Deep Learning

Deep learning models have achieved state-of-the-art performances on many...

Tuan Ngo Nguyen, et al. ∙

research

∙ 10/24/2019

Extending Event Detection to New Types with Learning from Keywords

Traditional event detection classifies a word or a phrase in a given sen...

Viet Dac Lai, et al. ∙

research

∙ 07/07/2019

Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control

Relation Extraction (RE) is one of the fundamental tasks in Information ...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 07/07/2019

Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures

Event factuality prediction (EFP) is the task of assessing the degree to...

Amir Pouran Ben Veyseh, et al. ∙

research

∙ 12/01/2018

One for All: Neural Joint Modeling of Entities and Events

The previous work for event extraction has mainly focused on the predict...

Trung Minh Nguyen, et al. ∙

research

∙ 11/30/2018

Systematic Generalization: What Is Required and Can It Be Learned?

Numerous models for grounded language understanding have been recently p...

Dzmitry Bahdanau, et al. ∙

research

∙ 10/18/2018

BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop

Allowing humans to interactively train artificial agents to understand l...

Maxime Chevalier-Boisvert, et al. ∙

research

∙ 07/09/2018

Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMs

Finding names of people killed by police has become increasingly importa...

Minh Nguyen, et al. ∙

research

∙ 05/03/2018

A Deep Learning Model with Hierarchical LSTMs and Supervised Attention for Anti-Phishing

Anti-phishing aims to detect phishing content/documents in a pool of tex...

Minh Nguyen, et al. ∙

research

∙ 02/24/2016

Toward Mention Detection Robustness with Recurrent Neural Networks

One of the key challenges in natural language processing (NLP) is to yie...

Thien Huu Nguyen, et al. ∙

research

∙ 11/18/2015

Combining Neural Networks and Log-linear Models to Improve Relation Extraction

The last decade has witnessed the success of the traditional feature-bas...

Thien Huu Nguyen, et al. ∙

Thien Huu Nguyen

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