5 citations · 9 across the 6 of their papers we have counts for
7 papers
Generative-AI for XR Content Transmission in the Metaverse: Potential Approaches, Challenges, and a Generation-Driven Transmission Framework
Zhe Zhang, Yili Jiang, Xin Wei +3
How to efficiently transmit large volumes of Extended Reality (XR) content through current networks has been a major bottleneck in realizing the Metaverse. The recently emerging Ge…
ParaJSCC: A Parameterized Framework for Reusable Multimodal Joint Source-Channel Coding
Kemi Chen, Mingkai Chen, Youjia Chen +3
Multimodal signals, such as visual, audio, and tactile data, are increasingly maintained as persistent digital assets in immersive communication systems and digital twins. In these…
Agentic AI-Empowered Conversational Embodied Intelligence Networks in 6G
Mingkai Chen, Zijie Feng, Lei Wang +1
In the 6G era, semantic collaboration among multiple embodied intelligent devices (MEIDs) becomes crucial for complex task execution. However, existing systems face challenges in m…
Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models
Chuan Liu, Chunshu Wu, Shihui Cao +8
The rapid development of AI highlights the pressing need for sustainable energy, a critical global challenge for decades. Nuclear fusion, generally seen as an ultimate solution, ha…
Inertial Confinement Fusion Forecasting via Large Language Models
Mingkai Chen, Taowen Wang, Shihui Cao +10
Controlled fusion energy is deemed pivotal for the advancement of human civilization. In this study, we introduce , a novel integration of Large Language Models (…
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
Daoan Zhang, Junming Yang, Hanjia Lyu +4
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image input…
Aggregation of Disentanglement: Reconsidering Domain Variations in Domain Generalization
Daoan Zhang, Mingkai Chen, Chenming Li +2
Domain Generalization (DG) is a fundamental challenge for machine learning models, which aims to improve model generalization on various domains. Previous methods focus on generati…