An Empirical Investigation of Pre-Trained Deep Learning Model Reuse in the Scientific Process
A new study on arXiv investigates the reuse of pre-trained deep learning models (PTMs) within the scientific process, particularly in natural sciences. The research quantifies PTM utilization across 17,718 open-access papers, finding that "Biochemistry, Genetics and Molecular Biology" leads in PTM reuse. The study identifies "adaptation" as the most common reuse pattern and highlights the "testing" stage of the scientific process as most impacted by PTM integration. AI
IMPACT Demonstrates growing reliance on pre-trained models in scientific research, potentially lowering barriers to entry for complex analyses.