Harnessing the Power of Single-Cell Large Language Models with Parameter Efficient Fine-Tuning using scPEFT
Fei He, Ruixin Fei, Jordan Edward Krull, Yang Yu, Xinyu Zhang, Xianyu Wang, Hao Cheng, Mingyue Gao, Li Su, Yibo Chen, Jinpu Li, Baichuan Jin, Yuzhou Chang, Anjun Ma, Qin Ma, Dong He Xu
This paper introduces scPEFT, a parameter-efficient fine-tuning framework for scLLMs that improves task adaptation with reduced computational costs and enhances performance in disease-specific and cross-species analyses.
Nature Machine Intelligence · Dec 31, 2025Peer-reviewedCell Biology