Matrix-Transformation based Low-Rank Adaptation (MTLoRA): A brain-inspired method for parameter-efficient fine-tuning.
- DOI
- 10.1016/j.neunet.2026.108642
- Published
- 2026 Jul
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.108642,
title = {Matrix-Transformation based Low-Rank Adaptation (MTLoRA): A brain-inspired method for parameter-efficient fine-tuning.},
author = {Liang Y and Wang Y and Li Y and Zeng Y},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.108642},
url = {https://doi.org/10.1016/j.neunet.2026.108642}
}RIS
TY - JOUR TI - Matrix-Transformation based Low-Rank Adaptation (MTLoRA): A brain-inspired method for parameter-efficient fine-tuning. AU - Liang Y AU - Wang Y AU - Li Y AU - Zeng Y PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.108642 UR - https://doi.org/10.1016/j.neunet.2026.108642 ER -
APA
Y, L., Y, W., Y, L., & Y, Z. (2026). Matrix-Transformation based Low-Rank Adaptation (MTLoRA): A brain-inspired method for parameter-efficient fine-tuning.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.108642
Source records
- pubmed · retrieved 2026-09-26T08:37:13.243Z