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Article
Deep multimodal-based finger spelling recognition for Thai sign language: a new benchmark and model composition
Video-based sign language recognition is vital for improving communication for the deaf and hard of hearing. Creating and maintaining quality of Thai sign language video datasets is challenging due to a lack o...
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Article
Data Augmentation and Large Language Model for Legal Case Retrieval and Entailment
The Competition on Legal Information Extraction and Entailment (COLIEE) is a well-known international competition organized each year with the goal of applying machine learning algorithms and techniques in the...
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Chapter and Conference Paper
Vietnamese Elementary Math Reasoning Using Large Language Model with Refined Translation and Dense-Retrieved Chain-of-Thought
State-of-the-art large language models (LLMs) have succeeded in various tasks but still show limitations in solving math reasoning problems. Although this problem is actively studied in the English language, a...
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Chapter and Conference Paper
A Framework for Enhancing Statute Law Retrieval Using Large Language Models
Large language models (LLMs) have proven effective across a range of natural language processing tasks, yet their application in the legal domain, particularly for legal retrieval tasks, remains largely unexpl...
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Article
Parametric loss-based super-resolution for scene text recognition
Scene text image super-resolution (STISR) is regarded as the process of improving the image quality of low-resolution scene text images to improve text recognition accuracy. Recently, a text attention network ...
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Article
PhraseTransformer: an incorporation of local context information into sequence-to-sequence semantic parsing
Semantic parsing is a challenging task map** a natural language utterance to machine-understandable information representation. Recently, approaches using neural machine translation (NMT) have achieved many ...
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Chapter and Conference Paper
A Novel Pipeline to Enhance Question-Answering Model by Identifying Relevant Information
Question-Answering (QA) systems have increasingly drawn much interest in the research community. A significant number of methods and datasets are proposed for the QA tasks. One of the gold standard QA resource...
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Chapter and Conference Paper
NegT5: A Cross-Task Text-to-Text Framework for Negation in Question Answering
Negation is a fundamental grammatical construct that plays a crucial role in understanding QA tasks. It has been revealed that models trained with SQuAD1 still produce original responses when presented with ne...
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Chapter and Conference Paper
JNLP Team: Deep Learning Approaches for Tackling Long and Ambiguous Legal Documents in COLIEE 2022
Competition on Legal Information Extraction/Entailment (COLIEE) is an annual competition associated with the International Workshop in Juris-Informatics. The challenge for this competition is required not only...
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Article
Parametric regularization loss in super-resolution reconstruction
A noise-enhanced super-resolution generative adversarial network plus (nESRGAN+) was proposed to improve the enhanced super-resolution GAN (ESRGAN). The contributions of nESRGAN+ generate an impressive reconst...
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Article
A symbolic execution-based method to perform untargeted attack on feed-forward neural networks
DeepCheck is a symbolic execution-based method to attack feed-forward neural networks. However, in the untargeted attack, DeepCheck suffers from a low success rate due to the limitation of preserving neuron ac...
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Article
Abstract meaning representation for legal documents: an empirical research on a human-annotated dataset
Natural language processing techniques contribute more and more in analyzing legal documents recently, which supports the implementation of laws and rules using computers. Previous approaches in representing a...
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Chapter and Conference Paper
RVT-Transformer: Residual Attention in Answerability Prediction on Visual Question Answering for Blind People
Answerability Prediction on Visual Question Answering is an attractive and novel multi-modal task that can be regarded as a fundamental filter to eliminate the low-qualified samples in practical systems. Inste...
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Chapter and Conference Paper
Exploring Retriever-Reader Approaches in Question-Answering on Scientific Documents
As readers of scientific articles often read to answer specific questions, the task of Question-Answering (QA) in academic papers was proposed to evaluate the ability of intelligent systems to answer questions...
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Chapter and Conference Paper
Diversity-Oriented Route Planning for Tourists
Touring route planning is an essential part of e-tourism, and significantly aids the development of the tourism industry. Several models have been proposed to formalize the touring route-planning problem with ...
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Article
Cu-doped NaCu0.05Fe0.45Co0.5O2 as promising cathode material for Na-ion batteries: synthesis and characterization
In this work, Cu-doped NaFe0.5Co0.5O2 was easily prepared by a one-step solid-state reaction and studied the effect of copper salt precursors including CuCl2 and Cu(OAc)2 on the structure and electrochemical prop...
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Article
Encoded summarization: summarizing documents into continuous vector space for legal case retrieval
We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep n...
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Chapter and Conference Paper
A Classifier-Based Preordering Approach for English-Vietnamese Statistical Machine Translation
Reordering is of essential importance problem for phrase based statistical machine translation (SMT). In this paper, we propose an approach to automatically learn reordering rules as preprocessing step based o...
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Chapter and Conference Paper
A Deep Neural Architecture for Sentence-Level Sentiment Classification in Twitter Social Networking
This paper introduces a novel deep learning framework including a lexicon-based approach for sentence-level prediction of sentiment label distribution. We propose to first apply semantic rules and then use a D...
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Article
Feature weighting and SVM parameters optimization based on genetic algorithms for classification problems
Support Vector Machines (SVMs) are widely known as an efficient supervised learning model for classification problems. However, the success of an SVM classifier depends on the perfect choice of its parameters ...
