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Mixture-of-Experts

Papers

Showing 676700 of 1312 papers

TitleStatusHype
D^2MoE: Dual Routing and Dynamic Scheduling for Efficient On-Device MoE-based LLM Serving0
DADNN: Multi-Scene CTR Prediction via Domain-Aware Deep Neural Network0
DA-MoE: Towards Dynamic Expert Allocation for Mixture-of-Experts Models0
Data Expansion using Back Translation and Paraphrasing for Hate Speech Detection0
Decoding Knowledge Attribution in Mixture-of-Experts: A Framework of Basic-Refinement Collaboration and Efficiency Analysis0
Deep Gaussian Covariance Network0
Deep Learning Mixture-of-Experts Approach for Cytotoxic Edema Assessment in Infants and Children0
Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert Models0
Demystifying Softmax Gating Function in Gaussian Mixture of Experts0
Denoising OCT Images Using Steered Mixture of Experts with Multi-Model Inference0
Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models0
DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models0
Detecting Financial Fraud with Hybrid Deep Learning: A Mix-of-Experts Approach to Sequential and Anomalous Patterns0
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis0
Differentially Private Training of Mixture of Experts Models0
Direct Neural Machine Translation with Task-level Mixture of Experts models0
Discussion: Effective and Interpretable Outcome Prediction by Training Sparse Mixtures of Linear Experts0
Disguise without Disruption: Utility-Preserving Face De-Identification0
Distribution Learning for Molecular Regression0
Diverse Machine Translation with a Single Multinomial Latent Variable0
Diversified Dynamic Routing for Vision Tasks0
Diversifying the Expert Knowledge for Task-Agnostic Pruning in Sparse Mixture-of-Experts0
Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer0
Diversity-Promoting Bayesian Learning of Latent Variable Models0
Divide-and-Conquer: Cold-Start Bundle Recommendation via Mixture of Diffusion Experts0
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