AINeutralarXiv – CS AI · 9h ago6/10
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TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learning
Researchers introduce TAP (Two-Stage Adaptive Personalization), a novel federated learning framework that enables personalized fine-tuning of foundation models across clients with heterogeneous tasks and modalities. The method uses mismatched architectures to prevent cross-task interference and post-FL distillation to recover shared knowledge, advancing practical deployment of AI systems in distributed environments.