ADA-T5, a novel model was proposed by ; to overcome the scarcity in available data, they depended on generating pseudo-data in a model teached with few-shot prompting, description on SMILES molecules was provided for the model to learn predicting correct molecules from the desired properties. A retrieval-based prompting strategy led to excellence in the model's performance and to a continuous increase in data size.