Chang Ma

GIMLET is a graph-text model that uses natural language instructions for zero-shot molecule property prediction, outperforming baselines and approaching supervised models.

This paper introduces a method to improve protein representation learning by retrieving and integrating similar sequences without alignment, achieving faster and more accurate predictions than traditional methods.