3 papers
cs.DC2026
Low-Latency Federated Fine-Tuning for Large Language Models Over Wireless Networks
Zhiwen Pang, Kang Wei, Long Shi +3
Recently, federated large language models (LLMs) have drawn significant attention thanks to coupled capabilities of LLMs and federated learning (FL) that address privacy concerns i…
cs.MA2024
Content Caching-Assisted Vehicular Edge Computing Using Multi-Agent Graph Attention Reinforcement Learning
Jinjin Shen, Yan Lin, Yijin Zhang +3
In order to avoid repeated task offloading and realize the reuse of popular task computing results, we construct a novel content caching-assisted vehicular edge computing (VEC) fra…
cs.DC2024
Blockchain-aided wireless federated learning: Resource allocation and client scheduling
Jun Li, Weiwei Zhang, Kang Wei +4
Federated learning (FL) based on the centralized design faces both challenges regarding the trust issue and a single point of failure. To alleviate these issues, blockchain-aided d…