Modality-Decoupled Federated Learning for Privacy-Preserving Embodied Intelligence in 6G
FedMVLA is proposed, a modality-decoupled FL framework for privacy-preserving embodied intelligence in 6G networks that incorporates three mechanisms: modality-aware federated aggregation (MAFA), modality-aware privacy allocation (MAPA), and modality-aware communication compression (MACO), together with a modality-slic...
Zhuo-Dong Liu, Xiang-Yu Li, Chun-Hong Yuan et al.
· IEEE wireless communications · 0 citations