Edge Large AI Models: Collaborative Deployment and IoT Applications

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Edge Large AI Models: Revolutionizing 6G Networks

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Federated Fine-Tuning for Pre-Trained Foundation Models over Wireless Networks

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Joint Rank Optimization and Bandwidth Allocation for Heterogeneous Federated LoRA Fine-Tuning

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Learning to Beamform for Integrated Sensing and Communication: A Graph Neural Network With Implicit Projection Approach

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Microservice Migration in Hybrid Satellite-Terrestrial Networks for Autonomous Vehicles

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Federated Low-Rank Adaptation for Large Language Model Fine-Tuning Over Wireless Networks

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Federated Low-Rank Adaptation with Differential Privacy over Wireless Networks

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Latency-Minimal Decentralized LAM Training with Looped Transformers in Heterogeneous LEO Satellite Constellations

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SAI: Latency-Aware Satellite Edge LAM Inference with Looped Transformer

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Graph Attention-Based MADRL for Access Control and Resource Allocation in Wireless Networked Control Systems

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Over-the-Air Federated Graph Learning

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Scalable Hybrid Beamforming for Multi-User MISO Systems: A Graph Neural Network Approach

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Over-the-Air Computation Assisted Federated Learning with Progressive Training

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A Graph Neural Network Learning Approach to Optimize RIS-Assisted Federated Learning

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Knowledge-Guided Learning for Transceiver Design in Over-the-Air Federated Learning

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Machine Learning for Large-Scale Optimization in 6G Wireless Networks

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Trustworthy Federated Learning via Blockchain

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Energy-Efficient Federated Learning over Hierarchical Aerial Wireless Networks

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Learning to Beamform for Dual-Functional MIMO Radar-Communication Systems

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Decentralized Multi-Agent Power Control in Wireless Networks with Frequency Reuse

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GAN and Multi-Agent DRL Based Decentralized Traffic Light Signal Control

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Intelligent Traffic Network Control in the Era of Internet of Vehicles

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Joint traffic signal and connected vehicle control in IoV via deep reinforcement learning

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Global traffic state recovery via local observations with generative adversarial networks

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