2 citations · 3 across the 7 of their papers we have counts for
7 papers
Q-ShiftDP: A Differentially Private Parameter-Shift Rule for Quantum Machine Learning
Hoang M. Ngo, Nhat Hoang-Xuan, Quan Nguyen +3
Quantum Machine Learning (QML) promises significant computational advantages, but preserving training data privacy remains challenging. Classical approaches like differentially pri…
PAS : Prelim Attention Score for Detecting Object Hallucinations in Large Vision--Language Models
Nhat Hoang-Xuan, Minh Vu, My T. Thai +1
Large vision-language models (LVLMs) are powerful, yet they remain unreliable due to object hallucinations. In this work, we show that in many hallucinatory predictions the LVLM ef…
HalluField: Detecting LLM Hallucinations via Field-Theoretic Modeling
Minh Vu, Brian K. Tran, Syed A. Shah +3
Large Language Models (LLMs) exhibit impressive reasoning and question-answering capabilities. However, they often produce inaccurate or unreliable content known as hallucinations.…
LLM-assisted Concept Discovery: Automatically Identifying and Explaining Neuron Functions
Nhat Hoang-Xuan, Minh Vu, My T. Thai
Providing textual concept-based explanations for neurons in deep neural networks (DNNs) is of importance in understanding how a DNN model works. Prior works have associated concept…
TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval
Trung-Nghia Le, Tam V. Nguyen, Minh-Quan Le +30
3D object retrieval is an important yet challenging task that has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issu…
SketchANIMAR: Sketch-based 3D Animal Fine-Grained Retrieval
Trung-Nghia Le, Tam V. Nguyen, Minh-Quan Le +31
The retrieval of 3D objects has gained significant importance in recent years due to its broad range of applications in computer vision, computer graphics, virtual reality, and aug…