9 papers
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…
-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…
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-…
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…