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FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense
FedLSG, the first framework that integrates large language models (LLMs) into federated graph backdoor defense, introduces a graph and behavior to text grounding scheme that transforms local graph structures and client update behaviors into semantically rich natural language representations.
Decentralized Topology Robustness Optimization for IoT via Multi-Agent Graph Reinforcement Learning
The robustness of Internet of Things (IoT) communication topologies against internal failures and external perturbations is a fundamental prerequisite for maintaining system stability. This paper studies IoT topology robustness from two perspectives: robustness metric and optimization. Existing robustness metrics, prim...