6 citations · 33 across the 28 of their papers we have counts for
32 papers
Agentic Multi-Turn Reasoning: A Fairness Approach
Thanh-Dat Truong, Sankalp Pandey, Hugh Churchill +3
Recent advances in Large Language Models (LLMs) have enabled agentic systems capable of solving complex tasks through multi-turn planning, tool use, verification, and memory update…
-DPO: Fairness Direct Preference Optimization Approach to Continual Learning in Large Multimodal Models
Thanh-Dat Truong, Huu-Thien Tran, Jackson Cothren +2
Fairness in Continual Learning for Large Multimodal Models (LMMs) is an emerging yet underexplored challenge, particularly in the presence of imbalanced data distributions that can…
BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understanding
Xuan-Bac Nguyen, Thanh-Dat Truong, Pawan Sinha +1
Memory decay makes it harder for the human brain to recognize visual objects and retain details. Consequently, recorded brain signals become weaker, uncertain, and contain poor vis…
Directed-Tokens: A Robust Multi-Modality Alignment Approach to Large Language-Vision Models
Thanh-Dat Truong, Huu-Thien Tran, Tran Thai Son +2
Large multimodal models (LMMs) have gained impressive performance due to their outstanding capability in various understanding tasks. However, these models still suffer from some f…
MANGO: Multimodal Attention-based Normalizing Flow Approach to Fusion Learning
Thanh-Dat Truong, Christophe Bobda, Nitin Agarwal +1
Multimodal learning has gained much success in recent years. However, current multimodal fusion methods adopt the attention mechanism of Transformers to implicitly learn the underl…
BIMA: Bijective Maximum Likelihood Learning Approach to Hallucination Prediction and Mitigation in Large Vision-Language Models
Huu-Thien Tran, Thanh-Dat Truong, Khoa Luu
Large vision-language models have become widely adopted to advance in various domains. However, developing a trustworthy system with minimal interpretable characteristics of large-…
Insect-Foundation: A Foundation Model and Large Multimodal Dataset for Vision-Language Insect Understanding
Thanh-Dat Truong, Hoang-Quan Nguyen, Xuan-Bac Nguyen +3
Multimodal conversational generative AI has shown impressive capabilities in various vision and language understanding through learning massive text-image data. However, current co…
Towards Robust and Fair Vision Learning in Open-World Environments
Thanh-Dat Truong
The dissertation presents four key contributions toward fairness and robustness in vision learning. First, to address the problem of large-scale data requirements, the dissertation…
ED-SAM: An Efficient Diffusion Sampling Approach to Domain Generalization in Vision-Language Foundation Models
Thanh-Dat Truong, Xin Li, Bhiksha Raj +2
The Vision-Language Foundation Model has recently shown outstanding performance in various perception learning tasks. The outstanding performance of the vision-language model mainl…
EAGLE: Efficient Adaptive Geometry-based Learning in Cross-view Understanding
Thanh-Dat Truong, Utsav Prabhu, Dongyi Wang +4
Unsupervised Domain Adaptation has been an efficient approach to transferring the semantic segmentation model across data distributions. Meanwhile, the recent Open-vocabulary Seman…
Multi-view Action Recognition via Directed Gromov-Wasserstein Discrepancy
Hoang-Quan Nguyen, Thanh-Dat Truong, Khoa Luu
Action recognition has become one of the popular research topics in computer vision. There are various methods based on Convolutional Networks and self-attention mechanisms as Tran…
FALCON: Fairness Learning via Contrastive Attention Approach to Continual Semantic Scene Understanding
Thanh-Dat Truong, Utsav Prabhu, Bhiksha Raj +2
Continual Learning in semantic scene segmentation aims to continually learn new unseen classes in dynamic environments while maintaining previously learned knowledge. Prior studies…
Insect-Foundation: A Foundation Model and Large-scale 1M Dataset for Visual Insect Understanding
Hoang-Quan Nguyen, Thanh-Dat Truong, Xuan Bac Nguyen +3
In precision agriculture, the detection and recognition of insects play an essential role in the ability of crops to grow healthy and produce a high-quality yield. The current mach…
Fairness Continual Learning Approach to Semantic Scene Understanding in Open-World Environments
Thanh-Dat Truong, Hoang-Quan Nguyen, Bhiksha Raj +1
Continual semantic segmentation aims to learn new classes while maintaining the information from the previous classes. Although prior studies have shown impressive progress in rece…
Cross-view Action Recognition Understanding From Exocentric to Egocentric Perspective
Thanh-Dat Truong, Khoa Luu
Understanding action recognition in egocentric videos has emerged as a vital research topic with numerous practical applications. With the limitation in the scale of egocentric dat…
CoMaL: Conditional Maximum Likelihood Approach to Self-supervised Domain Adaptation in Long-tail Semantic Segmentation
Thanh-Dat Truong, Chi Nhan Duong, Pierce Helton +3
The research in self-supervised domain adaptation in semantic segmentation has recently received considerable attention. Although GAN-based methods have become one of the most popu…
CROVIA: Seeing Drone Scenes from Car Perspective via Cross-View Adaptation
Thanh-Dat Truong, Chi Nhan Duong, Ashley Dowling +3
Understanding semantic scene segmentation of urban scenes captured from the Unmanned Aerial Vehicles (UAV) perspective plays a vital role in building a perception model for UAV. Wi…
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding
Thanh-Dat Truong, Ngan Le, Bhiksha Raj +2
Although Domain Adaptation in Semantic Scene Segmentation has shown impressive improvement in recent years, the fairness concerns in the domain adaptation have yet to be well defin…
CONDA: Continual Unsupervised Domain Adaptation Learning in Visual Perception for Self-Driving Cars
Thanh-Dat Truong, Pierce Helton, Ahmed Moustafa +2
Although unsupervised domain adaptation methods have achieved remarkable performance in semantic scene segmentation in visual perception for self-driving cars, these approaches rem…
Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition
Thanh-Dat Truong, Chi Nhan Duong, Ngan Le +2
In this work, we investigate the problem of face reconstruction given a facial feature representation extracted from a blackbox face recognition engine. Indeed, it is a very challe…
Self-supervised Domain Adaptation in Crowd Counting
Pha Nguyen, Thanh-Dat Truong, Miaoqing Huang +3
Self-training crowd counting has not been attentively explored though it is one of the important challenges in computer vision. In practice, the fully supervised methods usually re…
OTAdapt: Optimal Transport-based Approach For Unsupervised Domain Adaptation
Thanh-Dat Truong, Naga Venkata Sai Raviteja Chappa, Xuan Bac Nguyen +3
Unsupervised domain adaptation is one of the challenging problems in computer vision. This paper presents a novel approach to unsupervised domain adaptations based on the optimal t…
DirecFormer: A Directed Attention in Transformer Approach to Robust Action Recognition
Thanh-Dat Truong, Quoc-Huy Bui, Chi Nhan Duong +4
Human action recognition has recently become one of the popular research topics in the computer vision community. Various 3D-CNN based methods have been presented to tackle both th…
BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
Thanh-Dat Truong, Chi Nhan Duong, Ngan Le +3
Semantic segmentation aims to predict pixel-level labels. It has become a popular task in various computer vision applications. While fully supervised segmentation methods have ach…