149 citations · 151 across the 4 of their papers we have counts for
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cs.LG2026
FourierMoE: Fourier Mixture-of-Experts Adaptation of Large Language Models
Juyong Jiang, Fan Wang, Hong Qi +2
Parameter-efficient fine-tuning (PEFT) has emerged as a crucial paradigm for adapting large language models (LLMs) under constrained computational budgets. However, standard PEFT m…
cs.LG2024★ 149 cited
A Survey on Mixture of Experts in Large Language Models
Weilin Cai, Juyong Jiang, Fan Wang +3
Large language models (LLMs) have garnered unprecedented advancements across diverse fields, ranging from natural language processing to computer vision and beyond. The prowess of…
cs.LG2024★ 2 cited
Shortcut-connected Expert Parallelism for Accelerating Mixture-of-Experts
Weilin Cai, Juyong Jiang, Le Qin +3
Expert parallelism has emerged as a key strategy for distributing the computational workload of sparsely-gated mixture-of-experts (MoE) models across multiple devices, enabling the…