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FactorLLM: Factorizing Knowledge via Mixture of Experts for Large
  Language Models

FactorLLM: Factorizing Knowledge via Mixture of Experts for Large Language Models

15 August 2024
Zhongyu Zhao
Menghang Dong
Rongyu Zhang
Wenzhao Zheng
Yunpeng Zhang
Huanrui Yang
Dalong Du
Kurt Keutzer
Shanghang Zhang
ArXivPDFHTML

Papers citing "FactorLLM: Factorizing Knowledge via Mixture of Experts for Large Language Models"

4 / 4 papers shown
Title
DistiLLM: Towards Streamlined Distillation for Large Language Models
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko
Sungnyun Kim
Tianyi Chen
SeYoung Yun
36
25
0
06 Feb 2024
ReLU Strikes Back: Exploiting Activation Sparsity in Large Language
  Models
ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models
Iman Mirzadeh
Keivan Alizadeh-Vahid
Sachin Mehta
C. C. D. Mundo
Oncel Tuzel
Golnoosh Samei
Mohammad Rastegari
Mehrdad Farajtabar
118
58
0
06 Oct 2023
Mixture of Attention Heads: Selecting Attention Heads Per Token
Mixture of Attention Heads: Selecting Attention Heads Per Token
Xiaofeng Zhang
Yikang Shen
Zeyu Huang
Jie Zhou
Wenge Rong
Zhang Xiong
MoE
85
42
0
11 Oct 2022
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
220
3,054
0
23 Jan 2020
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