5 papers
Federated Attention: A Distributed Paradigm for Collaborative LLM Inference over Edge Networks
Xiumei Deng, Zehui Xiong, Binbin Chen +3
Large language models (LLMs) are proliferating rapidly at the edge, delivering intelligent capabilities across diverse application scenarios. However, their practical deployment in…
Accelerating Privacy-Preserving Federated Learning in Large-Scale LEO Satellite Systems
Binquan Guo, Junteng Cao, Marie Siew +3
Large-scale low-Earth-orbit (LEO) satellite systems are increasingly valued for their ability to enable rapid and wide-area data exchange, thereby facilitating the collaborative tr…
Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC)
Nan Li, Wanting Yang, Marie Siew +4
Diffusion models (DMs) have emerged as powerful tools for high-quality content generation, yet their intensive computational requirements for inference pose challenges for resource…
Agent Network Protocol Technical White Paper
Gaowei Chang, Eidan Lin, Chengxuan Yuan +4
With the development of large models and autonomous decision-making AI, agents are rapidly becoming the new entities of the internet, following mobile apps. However, existing inter…
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
Yuecheng Li, Lele Fu, Tong Wang +6
To defend against privacy leakage of user data, differential privacy is widely used in federated learning, but it is not free. The addition of noise randomly disrupts the semantic…