Summary of Mixture Of a Million Experts, by Xu Owen He
Mixture of A Million Expertsby Xu Owen HeFirst submitted to arxiv on: 4 Jul 2024CategoriesMain:…
Summary of Terminating Differentiable Tree Experts, by Jonathan Thomm et al.
Terminating Differentiable Tree Expertsby Jonathan Thomm, Michael Hersche, Giacomo Camposampiero, Aleksandar Terzić, Bernhard Schölkopf, Abbas…
Summary of Let the Expert Stick to His Last: Expert-specialized Fine-tuning For Sparse Architectural Large Language Models, by Zihan Wang et al.
Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Modelsby…
Summary of Efficient Expert Pruning For Sparse Mixture-of-experts Language Models: Enhancing Performance and Reducing Inference Costs, by Enshu Liu et al.
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costsby Enshu…
Summary of A Teacher Is Worth a Million Instructions, by Nikhil Kothari et al.
A Teacher Is Worth A Million Instructionsby Nikhil Kothari, Ravindra Nayak, Shreyas Shetty, Amey Patil,…
Summary of A Closer Look Into Mixture-of-experts in Large Language Models, by Ka Man Lo et al.
A Closer Look into Mixture-of-Experts in Large Language Modelsby Ka Man Lo, Zeyu Huang, Zihan…
Summary of Peirce in the Machine: How Mixture Of Experts Models Perform Hypothesis Construction, by Bruce Rushing
Peirce in the Machine: How Mixture of Experts Models Perform Hypothesis Constructionby Bruce RushingFirst submitted…
Summary of Theory on Mixture-of-experts in Continual Learning, by Hongbo Li et al.
Theory on Mixture-of-Experts in Continual Learningby Hongbo Li, Sen Lin, Lingjie Duan, Yingbin Liang, Ness…
Summary of Interpretable Cascading Mixture-of-experts For Urban Traffic Congestion Prediction, by Wenzhao Jiang et al.
Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Predictionby Wenzhao Jiang, Jindong Han, Hao Liu, Tao…
Summary of Interpretable Preferences Via Multi-objective Reward Modeling and Mixture-of-experts, by Haoxiang Wang et al.
Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Expertsby Haoxiang Wang, Wei Xiong, Tengyang Xie, Han…