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cs.LG2026
DP-LAC: Lightweight Adaptive Clipping for Differentially Private Federated Fine-tuning of Language Models
Haaris Mehmood, Jie Xu, Karthikeyan Saravanan +2
Federated learning (FL) enables the collaborative training of large-scale language models (LLMs) across edge devices while keeping user data on-device. However, FL still exposes se…
cs.LG2025
Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models
Junyi Zhu, Ruicong Yao, Taha Ceritli +6
Current network training paradigms primarily focus on either centralized or decentralized data regimes. However, in practice, data availability often exhibits a hybrid nature, wher…