Hugging Face Trending Papers July 9, 2026

FedOPAL: One-Shot Federated Learning via Analytic Visual Prompt Tuning

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With the widespread deployment of basic models in edge intelligence, communication bandwidth has become a core bottleneck restricting the scalability of federated learning. Although one-shot federated learning alleviates this problem by minimizing communication rounds, existing iterative fine-tuning or knowledge distillation methods still face challenges such as high server-side computational costs and hyperparameter sensitivity.

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arXiv AI

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FedOPAL: One-Shot Federated Learning via Analytic Visual Prompt Tuning

Federated Learning for Feature Generalization with Convex Constraints

FedTopo: Relation-Level Topology Sharing for Model-Heterogeneous Federated Learning

FedCausal-Dyn: A Causal-Dynamic Paradigm for Federated Learning under Dynamic Feature Drift

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