School of Computing Science

We introduce‘FedHera: Towards Drift-Resilient Federated Fine-tuning with Heterogeneous Resources’, a resource-decoupled, drift-resilient federated fine-tuning method that enhances global knowledge transfer and local adaptation under client resource heterogeneity.

First published: 7 May 2026