arXiv cs.LG
· Papers
MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification
arXiv:2607.29462v1 Announce Type: cross Abstract: Adapting deep learning models to profound clinical heterogeneity typically relies on parameter-efficient fine-tuning (PEFT) to avoid the severe overfitting associated with full end-to-end network updates. Although PEFT successfully navigates limited data scenarios, it i