D-FROST: decentralized federated prompt-tuning via optimal transport for non-IID and imbalanced data
Read the original at arxiv.org→arXiv:2609.01802v1 Announce Type: new Abstract: Prompt tuning provides a parameter-efficient way to adapt foundation models (FMs) by freezing the pretrained backbone and updating only a small set of learnable...
Original headline: "D-FROST: Decentralized Federated pRompt-tuning via Optimal tranSporT for Non-IID and Imbalanced Data"
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- Sep 3, 04:00 UTC arXiv cs.LG lead source D-FROST: Decentralized Federated pRompt-tuning via Optimal tranSporT for Non-IID and Imbalanced Data