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Xiang-Yu Li

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#artificial intelligence Open access Sep 2026

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

Preprint Aug 2026

FedCGR: Federated Cross-Domain Generative Recommendation

FedCGR is proposed, a federated generative CDR framework that keeps the item language stable and makes adaptation explicit and consistently outperforms federated generative baselines and achieves competitive performance against strong sequential and federated CDR methods under both full-ranking and sampled evaluation p...

Zhuo-Dong Liu, Hugen Lv, Xiang-Yu Li et al. · 0 citations