4 papers
Modality-Decoupled Federated Learning for Privacy-Preserving Embodied Intelligence in 6G
Zhuodong Liu, Xiangyu Li, Chunhong Yuan +5
Sixth-generation (6G) wireless networks are expected to provide a key infrastructure for large-scale embodied intelligence, where heterogeneous robots collaborate through low-laten…
FedCGR: Federated Cross-Domain Generative Recommendation
Zhuodong Liu, Hugen Lv, Xiangyu Li +2
Cross-domain recommendation (CDR) transfers preference knowledge across related domains, but federated deployment makes cross-domain alignment difficult because the behavioral anch…
Dual-Granularity Orthogonal Disentanglement for Generalizable Audio Deepfake Detection
Zhuodong Liu, Hugen Lv, Xiangyu Li +1
Audio deepfake detectors often fail to generalize across speakers, as they learn speaker-identity features rather than synthesis artifacts, known as implicit identity leakage. Exis…
pFedUL: Layer-Aware Federated Unlearning for Personalized Federated Learning
Zhuodong Liu, Xiangyu Li, Zhihao Zhang
Federated unlearning (FU) enables the removal of specific data contributions from federated learning (FL) models to comply with regulations such as the General Data Protection Regu…