FedLore: Communication and Memory Efficient Federated Learning via Shared Gradient Low-Rank Projection.

arXiv:2610.01620v1 Announce Type: new Abstract: Federated training of foundation models is constrained by client memory and communication costs. LoRA-based methods reduce these costs through low-rank adapters, but their fixed rank budget can limit adaptation.