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cs.LG2026
MACS: Modality-Aware Capacity Scaling for Efficient Multimodal MoE Inference
Bo Li, Chuan Wu, Shaolin Zhu
Mixture-of-Experts Multimodal Large Language Models (MoE MLLMs) suffer from a significant efficiency bottleneck during Expert Parallelism (EP) inference due to the straggler effect…
cs.LG2026
TENP: Trapezoidal Expert Neuron Pruning For Mixture-of-Experts
Jiangyang He, Shaolin Zhu, Deyi Xiong
Mixture-of-Experts large language models (LLMs) scale efficiently through sparse activation, yet their deployment is fundamentally constrained by the large static parameter footpri…