activity
20152023
most citedRecent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey

161 citations · 525 across the 35 of their papers we have counts for

collaborators

40 papers

cs.CL2023★ 19 cited

CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages

Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai +5

The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Alo…

cs.CL2023★ 3 cited

Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback

Viet Dac Lai, Chien Van Nguyen, Nghia Trung Ngo +4

A key technology for the development of large language models (LLMs) involves instruction tuning that helps align the models' responses with human expectations to realize impressiv…

cs.CL2023

Question-Context Alignment and Answer-Context Dependencies for Effective Answer Sentence Selection

Minh Van Nguyen, Kishan KC, Toan Nguyen +3

Answer sentence selection (AS2) in open-domain question answering finds answer for a question by ranking candidate sentences extracted from web documents. Recent work exploits answ…

cs.CL2023★ 53 cited

ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning

Viet Dac Lai, Nghia Trung Ngo, Amir Pouran Ben Veyseh +4

Over the last few years, large language models (LLMs) have emerged as the most important breakthroughs in natural language processing (NLP) that fundamentally transform research an…

cs.CL2022

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

Amir Pouran Ben Veyseh, Minh Van Nguyen, Franck Dernoncourt +1

Event Detection (ED) is the task of identifying and classifying trigger words of event mentions in text. Despite considerable research efforts in recent years for English text, the…

cs.CL2022

MEE: A Novel Multilingual Event Extraction Dataset

Amir Pouran Ben Veyseh, Javid Ebrahimi, Franck Dernoncourt +1

Event Extraction (EE) is one of the fundamental tasks in Information Extraction (IE) that aims to recognize event mentions and their arguments (i.e., participants) from text. Due t…

cs.CL2022★ 15 cited

Textual Data Augmentation for Patient Outcomes Prediction

Qiuhao Lu, Dejing Dou, Thien Huu Nguyen

Deep learning models have demonstrated superior performance in various healthcare applications. However, the major limitation of these deep models is usually the lack of high-quali…

cs.CL2022

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

Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen

Streaming videos is one of the methods for creators to share their creative works with their audience. In these videos, the streamer share how they achieve their final objective by…

cs.CL2022★ 1 cited

Improving Keyphrase Extraction with Data Augmentation and Information Filtering

Amir Pouran Ben Veyseh, Nicole Meister, Franck Dernoncourt +1

Keyphrase extraction is one of the essential tasks for document understanding in NLP. While the majority of the prior works are dedicated to the formal setting, e.g., books, news o…

cs.CL2022★ 2 cited

Symlink: A New Dataset for Scientific Symbol-Description Linking

Viet Dac Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt +1

Mathematical symbols and descriptions appear in various forms across document section boundaries without explicit markup. In this paper, we present a new large-scale dataset that e…

cs.CL2022★ 1 cited

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

Amir Pouran Ben Veyseh, Nicole Meister, Seunghyun Yoon +3

Acronym extraction is the task of identifying acronyms and their expanded forms in texts that is necessary for various NLP applications. Despite major progress for this task in rec…

cs.CL2022★ 1 cited

SemEval 2022 Task 12: Symlink- Linking Mathematical Symbols to their Descriptions

Viet Dac Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt +1

Given the increasing number of livestreaming videos, automatic speech recognition and post-processing for livestreaming video transcripts are crucial for efficient data management…

cs.CL2022★ 1 cited

FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction

Minh Van Nguyen, Nghia Trung Ngo, Bonan Min +1

This paper presents FAMIE, a comprehensive and efficient active learning (AL) toolkit for multilingual information extraction. FAMIE is designed to address a fundamental problem in…

cs.CL2021

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

Qiuhao Lu, Thien Huu Nguyen, Dejing Dou

Unplanned intensive care unit (ICU) readmission rate is an important metric for evaluating the quality of hospital care. Efficient and accurate prediction of ICU readmission risk c…

cs.CL2021★ 161 cited

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

Bonan Min, Hayley Ross, Elior Sulem +6

Large, pre-trained transformer-based language models such as BERT have drastically changed the Natural Language Processing (NLP) field. We present a survey of recent work that uses…

cs.CL2021★ 1 cited

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

Minh Van Nguyen, Viet Dac Lai, Thien Huu Nguyen

Existing works on information extraction (IE) have mainly solved the four main tasks separately (entity mention recognition, relation extraction, event trigger detection, and argum…

cs.CL2021

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

Amir Pouran Ben Veyseh, Franck Dernoncourt, Walter Chang +1

Acronyms and abbreviations are the short-form of longer phrases and they are ubiquitously employed in various types of writing. Despite their usefulness to save space in writing an…

cs.CL2021★ 12 cited

Acronym Identification and Disambiguation Shared Tasks for Scientific Document Understanding

Amir Pouran Ben Veyseh, Franck Dernoncourt, Thien Huu Nguyen +2

Acronyms are the short forms of longer phrases and they are frequently used in writing, especially scholarly writing, to save space and facilitate the communication of information.…

cs.CL2021★ 3 cited

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

Minh Van Nguyen, Viet Dac Lai, Amir Pouran Ben Veyseh +1

We introduce Trankit, a light-weight Transformer-based Toolkit for multilingual Natural Language Processing (NLP). It provides a trainable pipeline for fundamental NLP tasks over 1…

cs.LG2020★ 2 cited

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

Thu Nguyen, Duy Phung, Minh Hoai +1

Personality image captioning (PIC) aims to describe an image with a natural language caption given a personality trait. In this work, we introduce a novel formulation for PIC based…

cs.CL2020

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

Amir Pouran Ben Veyseh, Franck Dernoncourt, Quan Hung Tran +1

Acronyms are the short forms of phrases that facilitate conveying lengthy sentences in documents and serve as one of the mainstays of writing. Due to their importance, identifying…

cs.CL2020★ 9 cited

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

Viet Dac Lai, Tuan Ngo Nguyen, Thien Huu Nguyen

Recent studies on event detection (ED) haveshown that the syntactic dependency graph canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per-form…

cs.CL2020

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

Amir Pouran Ben Veyseh, Tuan Ngo Nguyen, Thien Huu Nguyen

The goal of Event Argument Extraction (EAE) is to find the role of each entity mention for a given event trigger word. It has been shown in the previous works that the syntactic st…

cs.CL2020★ 1 cited

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

Amir Pouran Ben Veyseh, Nasim Nour, Franck Dernoncourt +3

Aspect-based Sentiment Analysis (ABSA) seeks to predict the sentiment polarity of a sentence toward a specific aspect. Recently, it has been shown that dependency trees can be inte…