Author

Zhang Liu

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Jul 2026

HermesHFL: Incentive-Compatible Hierarchical Federated Unlearning for Dynamic LLM Fine-Tuning

Her HermesHFL, a hierarchical federated learning framework that supports selective unlearning, dynamic client participation, and client reintegration for scalable LLM fine-tuning via parameter-efficient fine-tuning (PEFT) with LoRA, is proposed and developed.

Chenxi Sun, Minghui Liwang, Wu-Si He et al. · arXiv.org · 0 citations