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cs.LG2025
FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning
Tao Shen, Zexi Li, Didi Zhu +3
Federated learning (FL) is a machine learning paradigm that allows multiple clients to collaboratively train a shared model without exposing their private data. Data heterogeneity…
cs.LG2025
Text2Weight: Bridging Natural Language and Neural Network Weight Spaces
Bowen Tian, Wenshuo Chen, Zexi Li +3
How far are we really from automatically generating neural networks? While neural network weight generation shows promise, current approaches struggle with generalization to unseen…