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Geometry-Informed Parameter-Efficient Fine-Tuning of Pre-trained Molecular GNNs for Blood-Brain Barrier Permeability Prediction

arXiv cs.LG ↗ · 2026-08-06 缓存

This paper introduces BBBP-GeoPEFT, a geometry-informed parameter-efficient fine-tuning framework for pre-trained molecular GNNs targeting blood-brain barrier permeability prediction, achieving competitive performance while updating only 10.1% of parameters.

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