BeamVLM for Low-altitude Economy: Generative Beam Prediction via Vision-language Models
Southern University of Science and Technology（南方科技大学）；ShanghaiTech University（上海科技大学）；The Chinese University of Hong Kong (Shenzhen)（香港中文大学（深圳））；Beijing Institute of Technology（北京理工大学）
For low-altitude economy (LAE), fast and accurate beam prediction between high-mobility unmanned aerial vehicles (UAVs) and ground base stations is of paramount importance, which ensures seamless coverage and reliable communications. However, existing deep learning-based beam prediction methods lack high-level semantic understanding of dynamic environments, resulting in poor generalization. On the other hand, the emerging large language model (LLM) based approaches show promise in enhancing generalization, but they typically lack rich environmental perception, thereby failing to capture fine-grained spatial semantics essential for precise beam alignment. To tackle these limitations, we propose in this correspondence a novel end-to-end generative framework for beam prediction, called BeamVLM, which treats beam prediction as a vision question answering task capitalizing on powerful existing vision-language models (VLMs). By projecting raw visual patches directly into the language domain and judiciously designing an instructional prompt, the proposed BeamVLM enables the VLM to jointly reason over UAV trajectories and environmental context. Last, experimental results on real-world datasets demonstrate that the proposed BeamVLM outperforms state-of-the-art methods in prediction accuracy and also exhibits superior generalization for other scenarios such as vehicle-to-infrastructure (V2I) beam prediction.
UAV Control and Communication Enabled Low-Altitude Economy: Challenges, Resilient Architecture and Co-design Strategies
School of Information Science and Technology, Harbin Institute of Technology, Shenzhen（哈尔滨工业大学深圳校区信息科学与技术学院）；Information System Technology and Design, Singapore University of Technology and Design（新加坡科技设计大学信息系统技术设计系）；ChinaTelecom Singapore Innovation Research Institute（中国电信新加坡创新研究院）；Information System Technology and Design Pillar, Singapore University of Technology and Design, Singapore（新加坡科技设计大学信息系统技术设计支柱）
Multi-Agent Collaborative Intrusion Detection for Low-Altitude Economy IoT: An LLM-Enhanced Agentic AI Framework
Jilin University（吉林大学）；Nanyang Technological University（南洋理工大学）；Edith Cowan University（伊迪丝科文大学）；the University of Technology Sydney（悉尼科技大学）；The University of Sydney（悉尼大学）；Tohoku University（东北大学）
Agentic AI for Embodied-enhanced Beam Prediction in Low-Altitude Economy Networks
School of Electronic Science and Engineering, South China Normal University（南方科技大学电子科学与工程学院）；School of Intelligent Engineering, Shaoguan university（韶关大学智能工程学院）；School of Automation, Guangdong University of Technology（广东工业大学自动化学院）
Agentic Satellite-Augmented Low-Altitude Economy and Terrestrial Networks: A Survey on Generative Approaches
School of Information and Electronics, Beijing Institute of Technology（信息与电子学院，北京理工大学）；College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；Department of Electrical and Computer Engineering, Sungkyunkwan University（电气与计算机工程系，首尔大学）；School of Electrical and Computer Engineering, University of Sydney（电气与计算机工程学院，悉尼大学）；School of Electrical and Electronics Engineering, Nanyang Technological University（电气与电子工程学院，南洋理工大学）；School of Cyberspace Science and Technology, Beijing Institute of Technology（网络空间科学与技术学院，北京理工大学）
Integrated Sensing and Communications for Low-Altitude Economy: A Deep Reinforcement Learning Approach
City University of Hong Kong（香港城市大学）；The Hong Kong Polytechnic University（香港理工大学）；Shanghai Jiao Tong University（上海交通大学）；Xiamen University（厦门大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Future Network of Intelligence Institute（深圳未来智能网络研究院）；Guangdong Provincial Key Laboratory of Future Networks of Intelligence（广东省未来智能网络重点实验室）
Edge-Assisted Multi-View Localization for Low-Altitude Economy under GPS-Challenged Environments
The Hong Kong University of Science and Technology（香港科技大学）；City University of Hong Kong（香港城市大学）；Zhejiang University（浙江大学）；Lingnan University（岭南大学）；Beihang University（北京航空航天大学）
Low-altitude Multi-UAV-assisted Data Collection and Semantic Forwarding for Post-Disaster Relief
Jilin University（吉林大学）；Nanyang Technological University（南洋理工大学）；Southern University of Science and Technology（南方科技大学）；University of Sydney（悉尼大学）；Tohoku University（东北大学）
Joint Task Offloading and Resource Allocation in Low-Altitude MEC via Graph Attention Diffusion
School of Computer Science, Northwestern Polytechnical University（西北工业大学计算机学院）；School of Cyber Engineering, Xidian University（西安电子科技大学电子工程学院）；Center for 6G Technology, Khalifa University of Science and Technology（卡塔尔科学技术大学6G技术中心）；School of Electrical and Electronics Engineering, Nanyang Technological University（南洋理工大学电子与电气工程学院）
A Disentangled Representation Learning Framework for Low-altitude Network Coverage Prediction
School of Information Science and Engineering, Southeast University（东南大学信息科学与工程学院）；College of Physics, Nanjing University of Aeronautics and Astronautics（南京航空航天大学物理学院）；Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong-Shenzhen（香港中文大学（深圳）大数据研究院）；Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics（南京航空航天大学电磁频谱空间动态认知系统重点实验室）
SkyChain Intelligence: A Blockchain-Secured Multi-Agent DRL Framework for Low-Altitude Embodied Artificial Intelligence
WeBank-NTU Joint Research Institute on Fintech, Nanyang Technological University（微众-南洋理工大学金融科技联合研究院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）；School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）理学院）；School of Information and Communication Engineering, University of Electronic Science and Technology of China（电子科技大学信息与通信工程学院）；School of Electrical and Computer Engineering, University of Sydney（悉尼大学电气与计算机工程学院）；Graduate School of Information Sciences, Tohoku University（东北大学信息科学研究科）；Department of Electrical and Computer Engineering, Sungkyunkwan University（成均馆大学电气与计算机工程系）
Task Delay and Energy Consumption Minimization for Low-altitude MEC via Evolutionary Multi-objective Deep Reinforcement Learning
College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）；College of Software, Jilin University（吉林大学软件学院）；Department of Electrical and Computer Engineering, Auburn University（奥本大学电气与计算机工程系）
