2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2025
MoE-SpeQ: Speculative Quantized Decoding with Proactive Expert Prefetching and Offloading for Mixture-of-Experts
Wenfeng Wang, Jiacheng Liu, Xiaofeng Hou +5
The immense memory requirements of state-of-the-art Mixture-of-Experts (MoE) models present a significant challenge for inference, often exceeding the capacity of a single accelera…
cs.LG2024★ 2 cited
HOBBIT: A Mixed Precision Expert Offloading System for Fast MoE Inference
Peng Tang, Jiacheng Liu, Xiaofeng Hou +5
The Mixture-of-Experts (MoE) architecture has demonstrated significant advantages in the era of Large Language Models (LLMs), offering enhanced capabilities with reduced inference…