The Goldilocks Paradigm: Comparing Classical Machine Learning, Large Language Models, And Few-shot Learning For Drug Discovery Applications

This article discusses the use of different machine learning techniques in drug discovery and compares their performance on datasets of varying sizes and chemical diversities. The authors propose a “Goldilocks learning paradigm” to help select the most suitable modeling method based on dataset characteristics.