Guest Editors
Dr. Thien Khai Tran
Email: thientk@huflit.edu.vn
Affiliation: Ho Chi Minh City University of Foreign Languages and Information Technology (HUFLIT), Ho Chi Minh City, Vietnam
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Research Interests: artificial intelligence; natural language processing; data science; machine learnin; deep learning
Dr. Kiet Van Nguyen
Email: kietnv@uit.edu.vn
Affiliation: The Information Science and Engineering Faculty at University of Information Technology, Vietnam National University, Ho Chi Minh City, Vietnam
Homepage:
Research Interests: computational linguistics; data science; artificial intelligence; vietnamese
Dr. Le Ha An
Email: anhl@huflit.edu.vn
Affiliation: Ho Chi Minh City University of Foreign Languages and Information Technology (HUFLIT), Ho Chi Minh City, Vietnam
Homepage:
Research Interests: the applications of NLP, such as multiple-choice-questions generation and analysis, automated scoring, and age-appropriateness classification
Dr. Hien Nguyen
Email: hzn5099@psu.edu
Affiliation: School of Science, Engineering, and Technology, Penn State Harrisburg, Middletown, PA 17057, USA
Homepage:
Research Interests: deep research in the field of natural language Processing (NLP
Summary
Natural Language Processing (NLP) is a dynamic and rapidly evolving field that has seen significant advancements in recent years. This special issue aims to gather cutting-edge research and practical applications that highlight the latest developments in NLP. We invite contributions that showcase novel methodologies, theoretical insights, and real-world applications that demonstrate the impact of these technologies on advancing NLP.
Topics of interest include, but are not limited to, advancements in Large Language Models (LLM), Knowledge Graphs (KG), Graph Neural Networks (GNN), and other emerging technologies in NLP. The goal is to provide a comprehensive overview of the state-of-the-art in NLP and to inspire further research in this exciting field.
Topics
Potential topics include, but are not limited to, the following:
• Advances in LLM architecture and training techniques
• Applications of LLM in various NLP tasks
• Development and integration of KG for enhanced information retrieval
• Novel GNN approaches for NLP
• Combining LLM, KG, and GNN to solve complex NLP problems
• Case studies and applications of LLM, KG, and GNN in industry and research
• Advances in other emerging NLP technologies and methodologies
• Low-resource methods for NLP
• Advances in Multimodal Vision Language Models for combining visual and linguistic data
• Challenges and future directions in NLP with emerging technologies
Keywords
Natural Language Processing, Large Language Models, Knowledge Graphs, Graph Neural Networks, Multimodal Vision Language Models , NLP Applications, Machine Learning, Deep Learning, Artificial Intelligence
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