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Dynamic Personalized Federated Learning with Adaptive Differential Privacy Xiyuan Y ang 1 Wenke Huang 1 Mang Y e
Despite its pilot progress, personalized federated learning with differential privacy still faces numerous challenges.
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ConStat: Performance-Based Contamination Detection in Large Language Models Jasper Dekoninck 1, Mark Niklas Müller 1,2, Martin Vechev 1 Department of Computer Science 1
Public benchmarks play an essential role in the evaluation of large language models.
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Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources
Optimal Transport distance to predict the model's performance for any data mixture
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FedFed: Feature Distillation against Data Heterogeneity in Federated Learning Zhiqin Y ang
Federated learning (FL) typically faces data heterogeneity, i.e., distribution shifting among clients. Sharing clients' information has shown great potentiality in mitigating data heterogeneity, yet incurs a dilemma in preserving privacy and promoting
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