4 papers indexed
Yaru Fu, Liang Ji, Sabita Maharjan, Tony Q. S. Quek
As artificial intelligence (AI) evolves from static perception to generative reasoning and autonomous agency, the fundamental principles of wireless communications are undergoing a paradigm shift. The classical Shannon paradigm, centered on reliable bit-level reconstruction for u…
Nuocheng Yang, Sihua Wang, Zihan Chen, Tony Q. S. Quek, Changchuan Yin
Embodied agent teams powered by heterogeneous large language models (LLMs) are being widely deployed in physical artificial intelligence such as smart factories, warehouses, and service robotics. To enable collaboration among such an agent team, efficient coordination mechanisms…
Yaheng Wang, Rui Meng, Xiaodong Xu, Yiming Liu, Feiliang Song, Linyuan Hu, et al.
Recent advances in generative artificial intelligence (AI) and embodied intelligence (EI) enable autonomous agents to interact with the physical world. However, scaling these systems into networks of multiple agents, namely the Internet of EI (IoEI), faces critical bottlenecks. T…
Chenyu Liu, Zhaoyang Zhang, Zirui Chen, Zhaohui Yang, Chunhui Feng, Tony Q. S. Quek
In wireless edge networks, split learning (SL) enables base station (BS) to utilize the distributed data and computing power across user equipments (UEs) to achieve collaborative model training while protecting local data privacy. However, the inherent sequential execution of com…