Summary of Remoe: Fully Differentiable Mixture-of-experts with Relu Routing, by Ziteng Wang et al.
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routingby Ziteng Wang, Jun Zhu, Jianfei ChenFirst submitted to…
ReMoE: Fully Differentiable Mixture-of-Experts with ReLU Routingby Ziteng Wang, Jun Zhu, Jianfei ChenFirst submitted to…
A Survey on Inference Optimization Techniques for Mixture of Experts Modelsby Jiacheng Liu, Peng Tang,…
Wonderful Matrices: Combining for a More Efficient and Effective Foundation Model Architectureby Jingze Shi, Bingheng…
Towards Adversarial Robustness of Model-Level Mixture-of-Experts Architectures for Semantic Segmentationby Svetlana Pavlitska, Enrico Eisen, J.…
Llama 3 Meets MoE: Efficient Upcyclingby Aditya Vavre, Ethan He, Dennis Liu, Zijie Yan, June…
Mixture of Experts Meets Decoupled Message Passing: Towards General and Adaptive Node Classificationby Xuanze Chen,…
MoE-CAP: Benchmarking Cost, Accuracy and Performance of Sparse Mixture-of-Experts Systemsby Yao Fu, Yinsicheng Jiang, Yeqi…
SAME: Learning Generic Language-Guided Visual Navigation with State-Adaptive Mixture of Expertsby Gengze Zhou, Yicong Hong,…
Convolutional Neural Networks and Mixture of Experts for Intrusion Detection in 5G Networks and beyondby…
Yi-Lightning Technical Reportby Alan Wake, Bei Chen, C.X. Lv, Chao Li, Chengen Huang, Chenglin Cai,…