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FedLogic: Interpretable Federated Multi-Domain Chain-of-Thought Prompt Selection for Large Language Models
To improve interpretability and explore the balance principle between generality and personalization under a multi-domain CoT prompt selection scenario, we propose the Federated Logic rule learning approach (FedLogic).
Federated Graph Neural Networks: Overview, Techniques and Challenges
This has led to the rapid development of the emerging research field of federated graph neural networks (FedGNNs).
Federated Learning for Personalized Humor Recognition
In this paper, we propose the FedHumor approach for the recognition of humorous content in a personalized manner through Federated Learning (FL).
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