7 citations · 23 across the 6 of their papers we have counts for
6 papers
GloCOM: A Short Text Neural Topic Model via Global Clustering Context
Quang Duc Nguyen, Tung Nguyen, Duc Anh Nguyen +3
Uncovering hidden topics from short texts is challenging for traditional and neural models due to data sparsity, which limits word co-occurrence patterns, and label sparsity, stemm…
SemiKong: Curating, Training, and Evaluating A Semiconductor Industry-Specific Large Language Model
Christopher Nguyen, William Nguyen, Atsushi Suzuki +10
Large Language Models (LLMs) have demonstrated the potential to address some issues within the semiconductor industry. However, they are often general-purpose models that lack the…
Enhancing Q&A with Domain-Specific Fine-Tuning and Iterative Reasoning: A Comparative Study
Zooey Nguyen, Anthony Annunziata, Vinh Luong +7
This paper investigates the impact of domain-specific model fine-tuning and of reasoning mechanisms on the performance of question-answering (Q&A) systems powered by large language…
Towards Comprehensive Vietnamese Retrieval-Augmented Generation and Large Language Models
Nguyen Quang Duc, Le Hai Son, Nguyen Duc Nhan +3
This paper presents our contributions towards advancing the state of Vietnamese language understanding and generation through the development and dissemination of open datasets and…
RaBiT: An Efficient Transformer using Bidirectional Feature Pyramid Network with Reverse Attention for Colon Polyp Segmentation
Nguyen Hoang Thuan, Nguyen Thi Oanh, Nguyen Thi Thuy +2
Automatic and accurate segmentation of colon polyps is essential for early diagnosis of colorectal cancer. Advanced deep learning models have shown promising results in polyp segme…
UGCANet: A Unified Global Context-Aware Transformer-based Network with Feature Alignment for Endoscopic Image Analysis
Pham Vu Hung, Nguyen Duy Manh, Nguyen Thi Oanh +2
Gastrointestinal endoscopy is a medical procedure that utilizes a flexible tube equipped with a camera and other instruments to examine the digestive tract. This minimally invasive…