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Scaling Laws for Fine-Grained Mixture of Experts

Scaling Laws for Fine-Grained Mixture of Experts

12 February 2024
Jakub Krajewski
Jan Ludziejewski
Kamil Adamczewski
Maciej Pióro
Michal Krutul
Szymon Antoniak
Kamil Ciebiera
Krystian Król
Tomasz Odrzygó'zd'z
Piotr Sankowski
Marek Cygan
Sebastian Jaszczur
    MoE
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Papers citing "Scaling Laws for Fine-Grained Mixture of Experts"

13 / 13 papers shown
Title
ORXE: Orchestrating Experts for Dynamically Configurable Efficiency
ORXE: Orchestrating Experts for Dynamically Configurable Efficiency
Qingyuan Wang
Guoxin Wang
B. Cardiff
Deepu John
23
0
0
07 May 2025
Position: Enough of Scaling LLMs! Lets Focus on Downscaling
Position: Enough of Scaling LLMs! Lets Focus on Downscaling
Ayan Sengupta
Yash Goel
Tanmoy Chakraborty
34
0
0
02 May 2025
Revisiting Transformers through the Lens of Low Entropy and Dynamic Sparsity
Revisiting Transformers through the Lens of Low Entropy and Dynamic Sparsity
Ruifeng Ren
Yong Liu
30
0
0
26 Apr 2025
MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core
MoE Parallel Folding: Heterogeneous Parallelism Mappings for Efficient Large-Scale MoE Model Training with Megatron Core
Dennis Liu
Zijie Yan
Xin Yao
Tong Liu
V. Korthikanti
...
Jiajie Yao
Chandler Zhou
David Wu
Xipeng Li
J. Yang
MoE
52
0
0
21 Apr 2025
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Yuqi Luo
Chenyang Song
Xu Han
Y. Chen
Chaojun Xiao
Zhiyuan Liu
Maosong Sun
47
3
0
04 Nov 2024
EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference
EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference
Yulei Qian
Fengcun Li
Xiangyang Ji
Xiaoyu Zhao
Jianchao Tan
K. Zhang
Xunliang Cai
MoE
50
2
0
16 Oct 2024
Scaling Laws for Predicting Downstream Performance in LLMs
Scaling Laws for Predicting Downstream Performance in LLMs
Yangyi Chen
Binxuan Huang
Yifan Gao
Zhengyang Wang
Jingfeng Yang
Heng Ji
LRM
41
7
0
11 Oct 2024
Aria: An Open Multimodal Native Mixture-of-Experts Model
Aria: An Open Multimodal Native Mixture-of-Experts Model
Dongxu Li
Yudong Liu
Haoning Wu
Yue Wang
Zhiqi Shen
...
Lihuan Zhang
Hanshu Yan
Guoyin Wang
Bei Chen
Junnan Li
MoE
49
48
0
08 Oct 2024
Scaling Optimal LR Across Token Horizons
Scaling Optimal LR Across Token Horizons
Johan Bjorck
Alon Benhaim
Vishrav Chaudhary
Furu Wei
Xia Song
46
4
0
30 Sep 2024
Small Language Models: Survey, Measurements, and Insights
Small Language Models: Survey, Measurements, and Insights
Zhenyan Lu
Xiang Li
Dongqi Cai
Rongjie Yi
Fangming Liu
Xiwen Zhang
Nicholas D. Lane
Mengwei Xu
ObjD
LRM
47
31
0
24 Sep 2024
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Nikhil Sardana
Jacob P. Portes
Sasha Doubov
Jonathan Frankle
LRM
220
64
0
31 Dec 2023
Mixture-of-Experts with Expert Choice Routing
Mixture-of-Experts with Expert Choice Routing
Yan-Quan Zhou
Tao Lei
Han-Chu Liu
Nan Du
Yanping Huang
Vincent Zhao
Andrew M. Dai
Zhifeng Chen
Quoc V. Le
James Laudon
MoE
145
323
0
18 Feb 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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