Beakcheol Jang
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View article: A Pivot-Enhanced Question Answering Framework: Using Iterative Sub-Question Decomposition and Answer-to-Question Verification
A Pivot-Enhanced Question Answering Framework: Using Iterative Sub-Question Decomposition and Answer-to-Question Verification Open
View article: IDQuAD: Infectious disease question and answering dataset
IDQuAD: Infectious disease question and answering dataset Open
While large language models (LLMs) have made significant advances in various fields, The study of applying LLMs to infectious disease-specific tasks has lagged behind. This study addresses this gap by introducing the Infectious Disease Que…
View article: Classification of fashion e-commerce products using ResNet-BERT multi-modal deep learning and transfer learning optimization
Classification of fashion e-commerce products using ResNet-BERT multi-modal deep learning and transfer learning optimization Open
As the fashion e-commerce markets rapidly develop, tens of thousands of products are registered daily on e-commerce platforms. Individual sellers register products after setting up a product category directly on a fashion e-commerce platfo…
View article: Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea
Accurate total consumer price index forecasting with data augmentation, multivariate features, and sentiment analysis: A case study in Korea Open
The Consumer Price Index (CPI) is a key economic indicator used by policymakers worldwide to monitor inflation and guide monetary policy decisions. In Korea, the CPI significantly impacts decisions on interest rates, fiscal policy framewor…
View article: Efficient Compressing and Tuning Methods for Large Language Models: A Systematic Literature Review
Efficient Compressing and Tuning Methods for Large Language Models: A Systematic Literature Review Open
Efficient compression and tuning techniques have become indispensable in addressing the increasing computational and memory demands of large language models (LLMs). While these models have demonstrated exceptional performance across a wide…
View article: Visual Question Answering: A Survey of Methods, Datasets, Evaluation, and Challenges
Visual Question Answering: A Survey of Methods, Datasets, Evaluation, and Challenges Open
Visual question answering (VQA) is a dynamic field of research that aims to generate textual answers from given visual and question information. It is a multimodal field that has garnered significant interest from the computer vision and n…
View article: Enhancing 3d Tooth Segmentation Using Curvature-Fps Point Cloud Down-Sampling
Enhancing 3d Tooth Segmentation Using Curvature-Fps Point Cloud Down-Sampling Open
View article: Enhancing 3D Tooth Segmentation Using Curvature-FPS Point Cloud Downsampling
Enhancing 3D Tooth Segmentation Using Curvature-FPS Point Cloud Downsampling Open
3D tooth segmentation is a crucial step in dental diagnosis, treatment planning, and digital dentistry. While deep learning-based models for 3D segmentation have shown success in various real-world applications, their direct application to…
View article: A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts
A Comprehensive Survey of Fake Text Detection on Misinformation and LM-Generated Texts Open
This paper presents a pioneering and comprehensive analysis of fake text, a pressing issue in the digital age, by categorizing it into two main types: Misinformation and LM-generated texts. It is the first study to systematically dissect a…
View article: Long-Term Epidemic Forecasting Using Correlation-Based Feature Selection and Triple Attention Lstm with Time-Differenced Multi-Regional Data
Long-Term Epidemic Forecasting Using Correlation-Based Feature Selection and Triple Attention Lstm with Time-Differenced Multi-Regional Data Open
View article: UniRAG: A Unified RAG Framework for Knowledge-Intensive Queries with Decomposition, Break-Down Reasoning, and Iterative Rewriting
UniRAG: A Unified RAG Framework for Knowledge-Intensive Queries with Decomposition, Break-Down Reasoning, and Iterative Rewriting Open
View article: Climate policy uncertainty and its impact on real estate market dynamics: A sectoral and regional analysis
Climate policy uncertainty and its impact on real estate market dynamics: A sectoral and regional analysis Open
This study explores the impact of Climate Policy Uncertainty (CPU) on real estate market volatility, utilizing the CPU index to assess how climate policy affects various real estate segments. It highlights the significant impact of CPU on …
View article: Forecasting Epidemic Spread with Recurrent Graph Gate Fusion Transformers
Forecasting Epidemic Spread with Recurrent Graph Gate Fusion Transformers Open
Predicting the unprecedented, nonlinear nature of COVID-19 presents a significant public health challenge. Recent advances in deep learning, such as graph neural networks (GNNs), recurrent neural networks (RNNs), and Transformers, have enh…
View article: Heterogeneous macroeconomic factors’ effects on stocks across sizes, styles, and sectors in the South Korean market
Heterogeneous macroeconomic factors’ effects on stocks across sizes, styles, and sectors in the South Korean market Open
Knowledge of the key macroeconomic variables that influence stock volatility across capital sizes, styles, and sectors can provide clues for investment strategies and policy decisions. We use the GARCH-MIDAS model with feature selection to…
View article: Enhancing Financial Sentiment Analysis Ability of Language Model via Targeted Numerical Change-Related Masking
Enhancing Financial Sentiment Analysis Ability of Language Model via Targeted Numerical Change-Related Masking Open
Sentiment analysis is a critical task that is highly beneficial to various financial tasks such as stock-price prediction, corporate credit rating, economic report analysis, and investment decision support. Researchers have used various me…
View article: Enhancing Machine-Generated Text Detection: Adversarial Fine-Tuning of Pre-Trained Language Models
Enhancing Machine-Generated Text Detection: Adversarial Fine-Tuning of Pre-Trained Language Models Open
Advances in large language models (LLMs) have revolutionized the natural language processing field. However, the text generated by LLMs can result in various issues, such as fake news, misinformation, and social media spam. In addition, de…
View article: Classification of mathematical test questions using machine learning on datasets of learning management system questions
Classification of mathematical test questions using machine learning on datasets of learning management system questions Open
Every student has a varied level of mathematical proficiency. Therefore, it is important to provide them with questions accordingly. Owing to advances in technology and artificial intelligence, the Learning Management System (LMS) has beco…
View article: Analysis of Psychological Factors Influencing Mathematical Achievement and Machine Learning Classification
Analysis of Psychological Factors Influencing Mathematical Achievement and Machine Learning Classification Open
This study analyzed the psychological factors that influence mathematical achievement in order to classify students’ mathematical achievement. Here, we employed linear regression to investigate the variables that contribute to mathematical…
View article: COVID-19 outbreak prediction using Seq2Seq + Attention and Word2Vec keyword time series data
COVID-19 outbreak prediction using Seq2Seq + Attention and Word2Vec keyword time series data Open
As of 2022, COVID-19, first reported in Wuhan, China, in November 2019, has become a worldwide epidemic, causing numerous infections and casualties and enormous social and economic damage. To mitigate its impact, various COVID-19 predictio…
View article: Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection
Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection Open
Crude oil plays an important role in the global economy, as it contributes one-third of the energy consumption worldwide. However, despite its importance in policymaking and economic development, forecasting its price is still challenging …
View article: Spectrum of Influence: Heterogeneous Macroeconomic Factors' Effects on Stocks Based on Size, Style, and Sector in the South Korean Market
Spectrum of Influence: Heterogeneous Macroeconomic Factors' Effects on Stocks Based on Size, Style, and Sector in the South Korean Market Open
View article: HSGA: A Hybrid LSTM-CNN Self-Guided Attention to Predict the Future Diagnosis From Discharge Narratives
HSGA: A Hybrid LSTM-CNN Self-Guided Attention to Predict the Future Diagnosis From Discharge Narratives Open
The prognosis of a patient’s re-admission and the forecast of future diagnoses is a critical task in the process of inferring clinical outcomes. The discharge summaries recorded in the Electronic Health Records (EHR) are stinking rich, but…
View article: Hsga: A Hybrid Lstm-Cnn Self-Guided Attention to Predict the Future Diagnosis from Discharge Narratives
Hsga: A Hybrid Lstm-Cnn Self-Guided Attention to Predict the Future Diagnosis from Discharge Narratives Open
View article: Evolution of Deep Learning-Based Sequential Recommender Systems: From Current Trends to New Perspectives
Evolution of Deep Learning-Based Sequential Recommender Systems: From Current Trends to New Perspectives Open
The recommender system which gets higher in practical use in applying the Apriori algorithm in the early 2000s has revolutionized our daily life as it currently is widely used by big-tech platform companies. In the early stages of the deve…
View article: Classification of Fashion E-Commerce Products Based on Resnet-Bert Multi-Modal Deep Learning and Transfer Learning Optimization Methodology
Classification of Fashion E-Commerce Products Based on Resnet-Bert Multi-Modal Deep Learning and Transfer Learning Optimization Methodology Open
View article: Autoregressive Decoder With Extracted Gap Sessions for Sequential/Session-Based Recommendation
Autoregressive Decoder With Extracted Gap Sessions for Sequential/Session-Based Recommendation Open
Learning the complex relationships between items in a sequential recommendation system (SRS) and session-based recommendation system (SBRS) is critical for obtaining higher prediction scores. In recent studies, to capture item-item informa…
View article: Climate Policy Uncertainty and its Varied Effects on Real Estate Sectors: Evidence from Us Property Markets
Climate Policy Uncertainty and its Varied Effects on Real Estate Sectors: Evidence from Us Property Markets Open
View article: Effectively computing transition patterns with privacy-preserved trajectory datasets
Effectively computing transition patterns with privacy-preserved trajectory datasets Open
Recent advances in positioning techniques, along with the widespread use of mobile devices, make it easier to monitor and collect user trajectory information during their daily activities. An ever-growing abundance of data about trajectori…
View article: Accurate prediction of electricity consumption using a hybrid CNN-LSTM model based on multivariable data
Accurate prediction of electricity consumption using a hybrid CNN-LSTM model based on multivariable data Open
The stress placed on global power supply systems by the growing demand for electricity has been steadily increasing in recent years. Thus, accurate forecasting of energy demand and consumption is essential to maintain the lifestyle and eco…
View article: Scalable Multi-Party Privacy-Preserving Gradient Tree Boosting over Vertically Partitioned Dataset with Outsourced Computations
Scalable Multi-Party Privacy-Preserving Gradient Tree Boosting over Vertically Partitioned Dataset with Outsourced Computations Open
Due to privacy concerns, multi-party gradient tree boosting algorithms have become widely popular amongst machine learning researchers and practitioners. However, limited existing works have focused on vertically partitioned datasets, and …