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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

F. Richard Yu

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6 papers indexed here

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#federated learning Nov 2026

Energy-Efficient Offloading, Caching, and Resource Allocation for Blockchain-Assisted Low-Altitude Flying Networks: An Integrated Federated Learning and MAPPO Approach

In 6G low-altitude edge intelligent networks, the proliferation of delay-sensitive Internet of Things (IoT) services exacerbates mutual interference among IoT devices, thereby reducing the efficiency of resource allocation. To address this challenge, we propose a blockchain-assisted federated learning (FL)-based four-l...

Zhi-Ran Wang, Bin-Tao Hu, Miguel López-Benítez et al. · 0 citations
2026

Joint Optimization of Handoff Control and Resource Block Allocation in Integrated GEO-Multibeam and LEO–UAV Networks

The integrated geostationary Earth orbit (GEO)-multibeam and low Earth orbit (LEO)-uncrewed aerial vehicle (UAV) network has emerged as a promising paradigm to enhance the coverage and capacity of terrestrial networks. However, due to the high dynamics of the network and the heterogeneous service demands of user equipm...

Feng Yang, Meng Li, Peng-Bo Si et al. · 0 citations
#artificial intelligence Conference Feb 2026

Beyond Pixels: A Vector-to-Graph Framework for Reliable Schematic Auditing

A Vector-to-Graph (V2G) pipeline that converts CAD diagrams into property graphs where nodes represent components and edges encode connectivity, making structural dependencies explicit and machine-auditable is proposed.

Cheng-Wei Ma, Zhen Tian, Zhou Zhou et al. · 1 citation
#artificial intelligence Mar 2026

Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation

ROSA2 is proposed, a framework that reformulates interaction as a joint optimization problem over the heterogeneous space of Words and Weights, and it is proved that this co-adaptation strictly reduces the required parameter shift for convergence.

Chen-Xing Wei, Hong Wang, Y. He et al. · 1 citation
#edge computing Oct 2026

Joint Optimization of Latency and Energy Consumption for Computing Task Offloading Based on Cooperative Multi-UAV and HAP Networks

The rapid expansion of computation-intensive applications renders current mobile edge computing (MEC) frameworks inadequate for delivering high-quality computing services in environments with sparse network infrastructure. Air-based stations, represented by low-altitude unmanned aerial vehicles (UAVs) and high-altitude...

Meng Li, Hao-Yu Wan, Su-Yu Lv et al. · 1 citation
2026

Lyapunov-Based Tri-Stage Online On-Demand Resource Allocation and Task Offloading in SAGIN

The rapid development of 6G makes space–air–ground integrated networks (SAGIN) a promising solution to the coverage and capacity limitations of traditional cellular systems. However, time-varying topologies, stochastic channels, imbalanced user demands, and limited resources hinder on-demand service provisioning in wid...

Luqiao Wang, Changle Li, Yao Zhang et al. · 0 citations

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