Author

Junlong Zhou

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Preprint Jul 2026

Scaling Synthetic-Image Pre-Training for Federated Fine-Tuning of Large Vision Models

FeDiSyn is proposed, a unified framework that holistically considers the interplay between pre-training and FedFT to minimize the overall LVM training time and introduces a scaling law for FedFT pre-training to determine the optimal number of synthetic images, balancing pre-training benefit against generation/pre-training cost.

Qianpiao Ma, Xiaozhu Song, Junlong Zhou et al. · 0 citations