Zhi-Qiang Xie

A Dual-Level Selective Unlearning Framework for Multi-Agent Decentralized Federated Learning

In agentic AI-enabled edge computing, decentralized federated learning (DFL) leverages peer-to-peer model aggregation to improve the performance of on-device large language models (LLMs) without introducing a single point of failure, thereby enhancing local agents’ capabilities for decision-making. To protect the right...