3 citations · 10 across the 26 of their papers we have counts for
31 papers
WaFIR: Wavelet-Fourier Mixture-of-Experts with Subband-Adaptive Routing for Blind All-in-One Image Restoration
Trong Nhan Nguyen, Vu Hoang Minh Doan, Thanh Dat Le +6
Blind all-in-one image restoration must adapt a shared model to heterogeneous and sometimes mixed degradations without a task label at test time. We introduce WaFIR, a decoder modu…
AMP Atlas: A Browser-Only Workbench for Antimicrobial Peptide Exploration and Interactive Helical-Wheel Design
Truong-Son Hy
Accessible research software can connect published antimicrobial peptide (AMP) records to sequence analysis, molecular visualization, and interactive design without requiring a ded…
From SQL to Knowledge Graphs: An LLM-Driven Multi-Agent Approach with Data Schema Improvement
Dinh-Khanh Pham, Quy-Anh Dang, Lam Mai Thanh +2
RDBMS (Relational Database Management System) databases face several limitations, including slow execution with multi-hop queries and a lack of explainability by graphical interpre…
Evaluating Agentic Bioinformatics through Function, Evidence, and Validation
Phuc Pham, Truong-Son Hy
Large language model agents increasingly plan, execute, and interpret biological analyses, yet fluent responses, successful tool calls, and benchmark performance alone do not estab…
A Hybrid Matheuristic Framework for the Chinese Postman Problem with Load-Dependent Costs
Thieu Khang Nguyen, Thu Huong Dang, Truong-Son Hy
The Chinese Postman Problem with load-dependent costs (CPP-LC) arises in real-world logistics and transportation systems where travel costs depend on vehicle load and energy consum…
Self-Evolving Multi-Agent Network for Industrial IoT Predictive Maintenance
Rebin Saleh, Khanh Pham Dinh, Balázs Villányi +1
Industrial IoT predictive maintenance requires systems capable of real-time anomaly detection without sacrificing interpretability or demanding excessive computational resources. T…
Efficient Deep Learning for Medical Imaging: Bridging the Gap Between High-Performance AI and Clinical Deployment
Cuong Manh Nguyen, Truong-Son Hy
Deep learning has revolutionized medical image analysis, playing a vital role in modern clinical applications. However, the deployment of large-scale models in real-world clinical…
Multimodal Machine Learning for Soft High-k Elastomers under Data Scarcity
Brijesh FNU, Viet Thanh Duy Nguyen, Ashima Sharma +3
Dielectric materials are critical building blocks for modern electronics such as sensors, actuators, and transistors. With rapid advances in soft and stretchable electronics for em…
RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models
Quy-Anh Dang, Chris Ngo, Truong-Son Hy
As large language models (LLMs) become integral to safety-critical applications, ensuring their robustness against adversarial prompts is paramount. However, existing red teaming d…
DiffPlace: A Conditional Diffusion Framework for Simultaneous VLSI Placement Beyond Sequential Paradigms
Kien Le Trung, Truong-Son Hy
Chip placement, a critical step in the VLSI physical design flow, directly impacts performance, power, and routability. Traditional chip placement methods, relying on analytical op…
LINKER: Learning Interactions Between Functional Groups and Residues With Chemical Knowledge-Enhanced Reasoning and Explainability
Phuc Pham, Viet Thanh Duy Nguyen, Truong-Son Hy
Accurate identification of interactions between protein residues and ligand functional groups is essential to understand molecular recognition and guide rational drug design. Exist…
DiFlow-TTS: Compact and Low-Latency Zero-Shot Text-to-Speech with Discrete Flow Matching
Ngoc-Son Nguyen, Thanh V. T. Tran, Hieu-Nghia Huynh-Nguyen +2
Zero-shot text-to-speech (TTS) has made significant progress in replicating unseen voices, yet balancing generation quality and inference efficiency remains challenging. Autoregres…
A Novel Framework for Automated Explain Vision Model Using Vision-Language Models
Phu-Vinh Nguyen, Tan-Hanh Pham, Chris Ngo +1
The development of many vision models mainly focuses on improving their performance using metrics such as accuracy, IoU, and mAP, with less attention to explainability due to the c…
Repeton: Structured Bug Repair with ReAct-Guided Patch-and-Test Cycles
Nguyen Phu Vinh, Anh Chung Hoang, Chris Ngo +1
Large Language Models (LLMs) have shown strong capabilities in code generation and comprehension, yet their application to complex software engineering tasks often suffers from low…
IQBench: How "Smart'' Are Vision-Language Models? A Study with Human IQ Tests
Tan-Hanh Pham, Phu-Vinh Nguyen, Dang The Hung +5
Although large Vision-Language Models (VLMs) have demonstrated remarkable performance in a wide range of multimodal tasks, their true reasoning capabilities on human IQ tests remai…
Topology-Guided Knowledge Distillation for Efficient Point Cloud Processing
Luu Tung Hai, Thinh D. Le, Zhicheng Ding +2
Point cloud processing has gained significant attention due to its critical role in applications such as autonomous driving and 3D object recognition. However, deploying high-perfo…
EquiHGNN: Scalable Rotationally Equivariant Hypergraph Neural Networks
Tien Dang, Truong-Son Hy
Molecular interactions often involve high-order relationships that cannot be fully captured by traditional graph-based models limited to pairwise connections. Hypergraphs naturally…
SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging
Tan-Hanh Pham, Chris Ngo, Trong-Duong Bui +3
Medical Visual Language Models have shown great potential in various healthcare applications, including medical image captioning and diagnostic assistance. However, most existing m…
RainbowPlus: Enhancing Adversarial Prompt Generation via Evolutionary Quality-Diversity Search
Quy-Anh Dang, Chris Ngo, Truong-Son Hy
Large Language Models (LLMs) exhibit remarkable capabilities but are susceptible to adversarial prompts that exploit vulnerabilities to produce unsafe or biased outputs. Existing r…
MOB-GCN: A Novel Multiscale Object-Based Graph Neural Network for Hyperspectral Image Classification
Tuan-Anh Yang, Truong-Son Hy, Phuong D. Dao
This paper introduces a novel multiscale object-based graph neural network called MOB-GCN for hyperspectral image (HSI) classification. The central aim of this study is to enhance…
Advances in Protein Representation Learning: Methods, Applications, and Future Directions
Viet Thanh Duy Nguyen, Truong-Son Hy
Proteins are complex biomolecules that play a central role in various biological processes, making them critical targets for breakthroughs in molecular biology, medical research, a…
A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors
Minh Ngoc Nguyen, Khai Le-Duc, Tan-Hanh Pham +7
Mental health problems such as stress, anxiety, and depression affect millions of people worldwide. These conditions are usually assessed using questionnaires, which rely on how pe…
Multimodal Contrastive Representation Learning in Augmented Biomedical Knowledge Graphs
Tien Dang, Viet Thanh Duy Nguyen, Minh Tuan Le +1
Biomedical Knowledge Graphs (BKGs) integrate diverse datasets to elucidate complex relationships within the biomedical field. Effective link prediction on these graphs can uncover…
Hybridising Reinforcement Learning and Heuristics for Hierarchical Directed Arc Routing Problems
Van Quang Nguyen, Quoc Chuong Nguyen, Thu Huong Dang +1
The Hierarchical Directed Capacitated Arc Routing Problem (HDCARP) is an extension of the Capacitated Arc Routing Problem (CARP), where the arcs of a graph are divided into classes…