892 citations · 1.1k across the 23 of their papers we have counts for
26 papers
SQLong: Enhanced NL2SQL for Longer Contexts with LLMs
Dai Quoc Nguyen, Cong Duy Vu Hoang, Duy Vu +5
Open-weight large language models (LLMs) have significantly advanced performance in the Natural Language to SQL (NL2SQL) task. However, their effectiveness diminishes when dealing…
Supporting Cross-language Cross-project Bug Localization Using Pre-trained Language Models
Mahinthan Chandramohan, Dai Quoc Nguyen, Padmanabhan Krishnan +1
Automatically locating a bug within a large codebase remains a significant challenge for developers. Existing techniques often struggle with generalizability and deployment due to…
Two-view Graph Neural Networks for Knowledge Graph Completion
Vinh Tong, Dai Quoc Nguyen, Dinh Phung +1
We present an effective graph neural network (GNN)-based knowledge graph embedding model, which we name WGE, to capture entity- and relation-focused graph structures. Given a knowl…
ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection
Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen +3
Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks. It, however, is also a challenging step that requires speci…
Automatic Post-Editing for Vietnamese
Thanh Vu, Dai Quoc Nguyen
Automatic post-editing (APE) is an important remedy for reducing errors of raw translated texts that are produced by machine translation (MT) systems or software-aided translation.…
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction
Dai Quoc Nguyen, Vinh Tong, Dinh Phung +1
We introduce a novel embedding model, named NoGE, which aims to integrate co-occurrence among entities and relations into graph neural networks to improve knowledge graph completio…
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen +1
We propose a simple yet effective embedding model to learn quaternion embeddings for entities and relations in knowledge graphs. Our model aims to enhance correlations between head…
Quaternion Graph Neural Networks
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Recently, graph neural networks (GNNs) have become an important and active research direction in deep learning. It is worth noting that most of the existing GNN-based methods learn…
A Self-Attention Network based Node Embedding Model
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Despite several signs of progress have been made recently, limited research has been conducted for an inductive setting where embeddings are required for newly unseen nodes -- a se…
A Vietnamese Question Answering System
Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham
Question answering systems aim to produce exact answers to users' questions instead of a list of related documents as used by current search engines. In this paper, we propose an o…
A Vietnamese Text-Based Conversational Agent
Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham
This paper introduces a Vietnamese text-based conversational agent architecture on specific knowledge domain which is integrated in a question answering system. When the question a…
A Fast Template-based Approach to Automatically Identify Primary Text Content of a Web Page
Dat Quoc Nguyen, Dai Quoc Nguyen, Son Bao Pham +1
Search engines have become an indispensable tool for browsing information on the Internet. The user, however, is often annoyed by redundant results from irrelevant Web pages. One r…
A Capsule Network-based Model for Learning Node Embeddings
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen +1
In this paper, we focus on learning low-dimensional embeddings for nodes in graph-structured data. To achieve this, we propose Caps2NE -- a new unsupervised embedding model leverag…
Universal Graph Transformer Self-Attention Networks
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
We introduce a transformer-based GNN model, named UGformer, to learn graph representations. In particular, we present two UGformer variants, wherein the first variant (publicized i…
A Relational Memory-based Embedding Model for Triple Classification and Search Personalization
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
Knowledge graph embedding methods often suffer from a limitation of memorizing valid triples to predict new ones for triple classification and search personalization problems. To t…
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen +2
In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object). Our CapsE represents each triple…
NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter
Thanh Vu, Dat Quoc Nguyen, Xuan-Son Vu +3
This paper describes our NIHRIO system for SemEval-2018 Task 3 "Irony detection in English tweets". We propose to use a simple neural network architecture of Multilayer Perceptron…
A Capsule Network-based Embedding Model for Search Personalization
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen +1
Search personalization aims to tailor search results to each specific user based on the user's personal interests and preferences (i.e., the user profile). Recent research approach…
VnCoreNLP: A Vietnamese Natural Language Processing Toolkit
Thanh Vu, Dat Quoc Nguyen, Dai Quoc Nguyen +2
We present an easy-to-use and fast toolkit, namely VnCoreNLP---a Java NLP annotation pipeline for Vietnamese. Our VnCoreNLP supports key natural language processing (NLP) tasks inc…
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen +1
In this paper, we propose a novel embedding model, named ConvKB, for knowledge base completion. Our model ConvKB advances state-of-the-art models by employing a convolutional neura…
From Word Segmentation to POS Tagging for Vietnamese
Dat Quoc Nguyen, Thanh Vu, Dai Quoc Nguyen +2
This paper presents an empirical comparison of two strategies for Vietnamese Part-of-Speech (POS) tagging from unsegmented text: (i) a pipeline strategy where we consider the outpu…
Sequence to Sequence Learning for Event Prediction
Dai Quoc Nguyen, Dat Quoc Nguyen, Cuong Xuan Chu +2
This paper presents an approach to the task of predicting an event description from a preceding sentence in a text. Our approach explores sequence-to-sequence learning using a bidi…
A Fast and Accurate Vietnamese Word Segmenter
Dat Quoc Nguyen, Dai Quoc Nguyen, Thanh Vu +2
We propose a novel approach to Vietnamese word segmentation. Our approach is based on the Single Classification Ripple Down Rules methodology (Compton and Jansen, 1990), where rule…
A Mixture Model for Learning Multi-Sense Word Embeddings
Dai Quoc Nguyen, Dat Quoc Nguyen, Ashutosh Modi +2
Word embeddings are now a standard technique for inducing meaning representations for words. For getting good representations, it is important to take into account different senses…