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cs.LG2025
Bridging On-Device and Cloud LLMs for Collaborative Reasoning: A Unified Methodology for Local Routing and Post-Training
Wenzhi Fang, Dong-Jun Han, Liangqi Yuan +2
Device-cloud collaboration holds promise for deploying large language models (LLMs), leveraging lightweight on-device models for efficiency while relying on powerful cloud models f…
cs.LG2025
Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization
Jianing Zhang, Evan Chen, Dong-Jun Han +2
Vertical Federated Learning (VFL) enables collaborative model training across feature-partitioned devices, yet its reliance on device-server information exchange introduces signifi…
cs.LG2025
Correcting Before Adapting: Gradient Correction for Federated Adaptive Optimization
Evan Chen, Shiqiang Wang, Jianing Zhang +4
Client-drift compensation methods mitigate the impact of data heterogeneity in federated learning (FL). While drift correction is well studied for stochastic gradient descent (SGD)…