MoEP: Compact and efficient sparsity with modular expert paths.
- DOI
- 10.1016/j.neunet.2026.109617
- Published
- 2026 Sep 11
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- no
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109617,
title = {MoEP: Compact and efficient sparsity with modular expert paths.},
author = {Tapaninaho J and Oussalah M},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109617},
url = {https://doi.org/10.1016/j.neunet.2026.109617}
}RIS
TY - JOUR TI - MoEP: Compact and efficient sparsity with modular expert paths. AU - Tapaninaho J AU - Oussalah M PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109617 UR - https://doi.org/10.1016/j.neunet.2026.109617 ER -
APA
J, T., & M, O. (2026). MoEP: Compact and efficient sparsity with modular expert paths.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109617
Source records
- pubmed · retrieved 2026-09-25T19:42:02.955Z
- europe-pmc · retrieved 2026-09-25T19:42:03.132Z