VLAI TEAM
Vision and Language in AI
Advancing AI in Vietnamese Language, Multimodal Learning, and NLP
About Us
Our Team
Duong Dinh Thang
Master Student
Natural Language Processing
Duong Nguyen Thuan
Master Student
Natural Language Processing
Duong Truong Binh
Researcher
Natural Language Processing
Nguyen Anh Khoi
Researcher
Natural Language Processing
Nguyen Phuc Thinh
Researcher
Natural Language Processing
Vu Yen Linh
Researcher
Natural Language Processing
Tran Hoang Duy
Researcher
Natural Language Processing
Pham Mai Hanh
Researcher
Natural Language Processing
Van Dinh Tue Thu
Researcher
Natural Language Processing
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🔬Research
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Natural Language Processing
Vietnamese language processing
Advanced research in Vietnamese NLP including tokenization, parsing, and semantic understanding
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Multimodal Learning
Vision + Language AI
Combining visual and textual information for comprehensive AI understanding
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Transfer Learning
Cross-lingual knowledge transfer
Enabling AI models to leverage knowledge across different languages and domains
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LLMs
Large Language Models
Exploring the capabilities and applications of large-scale language models
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Publications
Heterogeneous Transfer Learning Using Pre-trained Feature Mapping and Exchange
Duong Nguyen Thuan, Duong Dinh Thang
AICI 20242024
Transfer Learning (TL) is an efficient approach for training neural networks with improved performance and lower costs compared to training from scrat...
Read Full Paper→Enhancing Vietnamese VQA through Curriculum Learning on Raw and Augmented Text Representations
Nguyen Anh Khoi, Vu Yen Linh, Duong Nguyen Thuan, Duong Dinh Thang
AAAI 2025 Workshop2025
Visual Question Answering (VQA) is a multimodal task requiring reasoning across textual and visual inputs, which becomes particularly challenging in l...
Read Full Paper→An Automate Pipeline for Contructing a Vietnamese VQA-NLE Dataset
Duong Truong Binh, Duong Dinh Thang
ICISN 20252025
ViVQA-X is the Vietnamese version of the VQA-X dataset, designed for tasks in VQA-NLE in the Vietnamese language. This dataset was created to support ...
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