Inclusive Data Representation in Federated Learning: A Novel Approach Integrating Textual and Visual Prompt
Zihao Zhao,
Zhenpeng Shi,
Yang Liu
et al.
Abstract:Federated Learning (FL) is often impeded by communication overhead issues. Prompt tuning, as a potential solution, has been introduced to only adjust a few trainable parameters rather than the whole model. However, current single-modality prompt tuning approaches fail to comprehensively portray local clients' data. To overcome this limitation, we present Twin Prompt Federated learning (TPFL), a pioneering solution that integrates both visual and textual modalities, ensuring a more holistic representation of lo… Show more
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