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cs.LG2025
BuddyMoE: Exploiting Expert Redundancy to Accelerate Memory-Constrained Mixture-of-Experts Inference
Yun Wang, Lingyun Yang, Senhao Yu +5
Mixture-of-Experts (MoE) architectures scale language models by activating only a subset of specialized expert networks for each input token, thereby reducing the number of floatin…
cs.DC2025
Equinox: Holistic Fair Scheduling in Serving Large Language Models
Zhixiang Wei, James Yen, Jingyi Chen +11
We address the limitations of current LLM serving with a dual-counter framework separating user and operator perspectives. The User Fairness Counter measures quality of service via…