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A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications

A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications

10 March 2025
Siyuan Mu
Sen Lin
    MoE
ArXivPDFHTML

Papers citing "A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications"

3 / 203 papers shown
Title
Semantically Conditioned LSTM-based Natural Language Generation for
  Spoken Dialogue Systems
Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems
Tsung-Hsien Wen
Milica Gasic
N. Mrksic
Pei-hao Su
David Vandyke
S. Young
95
949
0
07 Aug 2015
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau
Kyunghyun Cho
Yoshua Bengio
AIMat
524
27,295
0
01 Sep 2014
Learning Factored Representations in a Deep Mixture of Experts
Learning Factored Representations in a Deep Mixture of Experts
David Eigen
MarcÁurelio Ranzato
Ilya Sutskever
MoE
78
374
0
16 Dec 2013
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