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cs.LG2025
Efficient Edge LLMs Deployment via HessianAware Quantization and CPU GPU Collaborative
Tuo Zhang, Ning Li, Xin Yuan +4
With the breakthrough progress of large language models (LLMs) in natural language processing and multimodal tasks, efficiently deploying them on resource-constrained edge devices…
cs.LG2025
FedPaI: Achieving Extreme Sparsity in Federated Learning via Pruning at Initialization
Haonan Wang, Zeli Liu, Kajimusugura Hoshino +3
Federated Learning (FL) enables distributed training on edge devices but faces significant challenges due to resource constraints in edge environments, impacting both communication…