Research map / Architectures and efficiency / Mixture of experts
MoEC: Mixture of Expert Clusters
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Closest papers by meaning
- Tight Clusters Make Specialized Experts (ICLR 2025 · similarity 0.92)
- Retraining-free Merging of Sparse MoE via Hierarchical Clustering (ICML 2025 · similarity 0.91)
- Pruning and Distilling Mixture-of-Experts into Dense Language Models (NeurIPS 2026 · similarity 0.91)
- Mixture of Experts Made Intrinsically Interpretable (ICML 2025 · similarity 0.90)
- Advancing Expert Specialization for Better MoE (NeurIPS 2025 · similarity 0.90)
- MoE-CAP: Benchmarking Cost, Accuracy and Performance of Sparse Mixture-of-Experts Systems (NeurIPS 2025 · similarity 0.90)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.