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cs.CV2025
MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping
Yushi Huang, Zining Wang, Zhihang Yuan +5
Mixture-of-Experts (MoE) Multimodal large language models (MLLMs) excel at vision-language tasks, but they suffer from high computational inefficiency. To reduce inference overhead…
cs.CV2024
QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning
Haoxuan Wang, Yuzhang Shang, Zhihang Yuan +3
The practical deployment of diffusion models is still hindered by the high memory and computational overhead. Although quantization paves a way for model compression and accelerati…