109 citations · 336 across the 15 of their papers we have counts for
5 papers · 1 filter
Federated Learning with Diffusion Models for Privacy-Sensitive Vision Tasks
Ye Lin Tun, Chu Myaet Thwal, Ji Su Yoon +3
Diffusion models have shown great potential for vision-related tasks, particularly for image generation. However, their training is typically conducted in a centralized manner, rel…
Contrastive encoder pre-training-based clustered federated learning for heterogeneous data
Ye Lin Tun, Minh N. H. Nguyen, Chu Myaet Thwal +2
Federated learning (FL) is a promising approach that enables distributed clients to collaboratively train a global model while preserving their data privacy. However, FL often suff…
An Efficient Federated Learning Framework for Training Semantic Communication System
Loc X. Nguyen, Huy Q. Le, Ye Lin Tun +4
Semantic communication has emerged as a pillar for the next generation of communication systems due to its capabilities in alleviating data redundancy. Most semantic communication…
Swin Transformer-Based Dynamic Semantic Communication for Multi-User with Different Computing Capacity
Loc X. Nguyen, Ye Lin Tun, Yan Kyaw Tun +4
Semantic communication has gained significant attention from researchers as a promising technique to replace conventional communication in the next generation of communication syst…
A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
Chaoning Zhang, Chenshuang Zhang, Sheng Zheng +14
As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) has made headlines everywhere because of its ability to analyze and create text, images, and beyond. With su…