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cs.LG2026
DyMoE: Dynamic Expert Orchestration with Mixed-Precision Quantization for Efficient MoE Inference on Edge
Yuegui Huang, Zhiyuan Fang, Weiqi Luo +3
Despite the computational efficiency of MoE models, the excessive memory footprint and I/O overhead inherent in multi-expert architectures pose formidable challenges for real-time…
cs.LG2025★ 1 cited
Klotski: Efficient Mixture-of-Expert Inference via Expert-Aware Multi-Batch Pipeline
Zhiyuan Fang, Yuegui Huang, Zicong Hong +5
Mixture of Experts (MoE), with its distinctive sparse structure, enables the scaling of language models up to trillions of parameters without significantly increasing computational…