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cs.LG2025
SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment
Yixin Song, Zhenliang Xue, Dongliang Wei +11
While frontier large language models (LLMs) continue to push capability boundaries, their deployment remains confined to GPU-powered cloud infrastructure. We challenge this paradig…
cs.LG2024
FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients
Han Liang, Ziwei Zhan, Weijie Liu +3
Federated Learning (FL) is a distributed machine learning paradigm that achieves a globally robust model through decentralized computation and periodic model synthesis, primarily f…