64 citations · 139 across the 25 of their papers we have counts for
25 papers
SLM, LLM or Agentic AI? Toward Intelligent UAV-Enabled WPT Systems in Low-Altitude Economy Networks
Feibo Jiang, Li Dong, Lei Mao +3
Unmanned Aerial Vehicles (UAVs) have become key enabling platforms for low-altitude economic networks, yet achieving efficient and adaptive optimization under resource-constrained…
Vision-Language-Action Models Meet World Models: Embodied Agentic AI for Low-Altitude Wireless Networks
Feibo Jiang, Li Dong, Lei Mao +4
Low-Altitude Wireless Networks (LAWNs), composed of Unmanned Aerial Vehicles (UAVs) and other aerial platforms, provide integrated perception, communication, and computation servic…
Aerial Agentic AI: Synergizing LLM and SLM for Low-Altitude Wireless Networks
Li Dong, Feibo Jiang, Kezhi Wang +3
Low-Altitude Wireless Networks (LAWNs), composed of Unmanned Aerial Vehicles (UAVs) and mobile terminals, are emerging as a critical extension of 6G. However, applying Large Langua…
Agentic AI Empowered Multi-UAV Trajectory Optimization in Low-Altitude Economy Networks
Feibo Jiang, Li Dong, Xitao Pan +2
This paper proposes a novel Agentic Retrieval-augmented generation with Mamba-Attention Integrated Transformer (ARMAIT) framework for multi-Unmanned Aerial Vehicle (UAV) trajectory…
From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications
Feibo Jiang, Cunhua Pan, Li Dong +3
With the advent of 6G communications, intelligent communication systems face multiple challenges, including constrained perception and response capabilities, limited scalability, a…
A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges
Feibo Jiang, Cunhua Pan, Li Dong +4
The 6G wireless communications aim to establish an intelligent world of ubiquitous connectivity, providing an unprecedented communication experience. Large artificial intelligence…
CommGPT: A Graph and Retrieval-Augmented Multimodal Communication Foundation Model
Feibo Jiang, Wanyun Zhu, Li Dong +4
Large Language Models (LLMs) possess human-level cognitive and decision-making capabilities, making them a key technology for 6G. However, applying LLMs to the communication domain…
FlashSAM: Lightweight Vision Model for Multi-UAV Token Communication in Low-Latitude Wireless Networks
Feibo Jiang, Siwei Tu, Li Dong +5
Token Communication (TokenCom) is a promising paradigm for low-altitude wireless networks, as it focuses on transmitting task-relevant core information, particularly in environment…
M4SC: An MLLM-based Multi-modal, Multi-task and Multi-user Semantic Communication System
Feibo Jiang, Siwei Tu, Li Dong +3
Multi-modal Large Language Models (MLLMs) are capable of precisely extracting high-level semantic information from multi-modal data, enabling multi-task understanding and generatio…
Large Generative Model-assisted Talking-face Semantic Communication System
Feibo Jiang, Siwei Tu, Li Dong +3
The rapid development of generative Artificial Intelligence (AI) continually unveils the potential of Semantic Communication (SemCom). However, current talking-face SemCom systems…
GAI-Enabled Explainable Personalized Federated Semi-Supervised Learning
Yubo Peng, Feibo Jiang, Li Dong +2
Federated learning (FL) is a commonly distributed algorithm for mobile users (MUs) training artificial intelligence (AI) models, however, several challenges arise when applying FL…
Personalized Federated Learning for Generative AI-Assisted Semantic Communications
Yubo Peng, Feibo Jiang, Li Dong +2
Semantic Communication (SC) focuses on transmitting only the semantic information rather than the raw data. This approach offers an efficient solution to the issue of spectrum reso…
Deep progressive reinforcement learning-based flexible resource scheduling framework for IRS and UAV-assisted MEC system
Li Dong, Feibo Jiang, Minjie Wang +2
The intelligent reflection surface (IRS) and unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is widely used in temporary and emergency scenarios. Our goal…
Visual Language Model based Cross-modal Semantic Communication Systems
Feibo Jiang, Chuanguo Tang, Li Dong +3
Semantic Communication (SC) has emerged as a novel communication paradigm in recent years, successfully transcending the Shannon physical capacity limits through innovative semanti…
Personalized Wireless Federated Learning for Large Language Models
Feibo Jiang, Li Dong, Siwei Tu +5
Large language models (LLMs) have driven profound transformations in wireless networks. However, within wireless environments, the training of LLMs faces significant challenges rel…
Large Generative Model Assisted 3D Semantic Communication
Feibo Jiang, Yubo Peng, Li Dong +4
Semantic Communication (SC) is a novel paradigm for data transmission in 6G. However, there are several challenges posed when performing SC in 3D scenarios: 1) 3D semantic extracti…
Large Language Model Enhanced Multi-Agent Systems for 6G Communications
Feibo Jiang, Li Dong, Yubo Peng +5
The rapid development of the Large Language Model (LLM) presents huge opportunities for 6G communications, e.g., network optimization and management by allowing users to input task…
Large AI Model Empowered Multimodal Semantic Communications
Feibo Jiang, Li Dong, Yubo Peng +4
Multimodal signals, including text, audio, image, and video, can be integrated into Semantic Communication (SC) systems to provide an immersive experience with low latency and high…
LAMBO: Large AI Model Empowered Edge Intelligence
Li Dong, Feibo Jiang, Yubo Peng +4
Next-generation edge intelligence is anticipated to benefit various applications via offloading techniques. However, traditional offloading architectures face several issues, inclu…
Large AI Model-Based Semantic Communications
Feibo Jiang, Yubo Peng, Li Dong +4
Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed reality, and the Internet of Everything. H…
Joint Optimization of Deployment and Trajectory in UAV and IRS-Assisted IoT Data Collection System
Li Dong, Zhibin Liu, Feibo Jiang +1
Unmanned aerial vehicles (UAVs) can be applied in many Internet of Things (IoT) systems, e.g., smart farms, as a data collection platform. However, the UAV-IoT wireless channels ma…
Distributed Resource Scheduling for Large-Scale MEC Systems: A Multi-Agent Ensemble Deep Reinforcement Learning with Imitation Acceleration
Feibo Jiang, Li Dong, Kezhi Wang +2
We consider the optimization of distributed resource scheduling to minimize the sum of task latency and energy consumption for all the Internet of things devices (IoTDs) in a large…
AI Driven Heterogeneous MEC System with UAV Assistance for Dynamic Environment -- Challenges and Solutions
Feibo Jiang, Kezhi Wang, Li Dong +3
By taking full advantage of Computing, Communication and Caching (3C) resources at the network edge, Mobile Edge Computing (MEC) is envisioned as one of the key enablers for the ne…
Stacked Auto Encoder Based Deep Reinforcement Learning for Online Resource Scheduling in Large-Scale MEC Networks
Feibo Jiang, Kezhi Wang, Li Dong +2
An online resource scheduling framework is proposed for minimizing the sum of weighted task latency for all the Internet of things (IoT) users, by optimizing offloading decision, t…