Preprint
Jul 2026
Toward Federated Multimodal Graph Foundation Models: A Topology-Aware Multimodal Alignment Framework
FedGAMMA is proposed, casting federated multimodal graph foundation learning as a two-stage semantic-structural alignment problem of federated pre-training and prompt-based fine-tuning, and outperforms competitive baselines accross multi-domain datasets on multiple tasks.
Xunkai Li, Guohao Fu, Yuming Ai et al.
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