As shown in Table , both O 2 -GEN and GaUDI have V&U&N of over 97% on the PAS dataset. However, on the COMPAS-1X dataset, GaUDI's unique and novelty performance drops significantly, while O 2 -GEN maintains a V&U&N close to 100%. To account for this difference, we characterized the two datasets using the molecular fingerprint method . The average fingerprint similarity of COMPAS-1X and PAS dataset (Figure .b and Supplementary Figure )) is 0.99 and 0.67 among their original molecules, respectively. This result indicates the molecular structure diversity of COMPAS-1X dataset is extremely limited, while the PAS dataset covers a much larger chemical space. GaUDI is strongly restricted by the diversity of the training data, while the 3D pretraining backbone of O 2 -GEN can provide prior information on pre-trained molecules. As a result (Figure .b), generated molecules showing an average molecular fingerprint with the similarity of 0.75. Further analysis revealed a significantly lower average fingerprint similarity of 0.05 between the generated molecules and those in the original dataset. A similar trend of change in molecular fingerprint similarity can also be observed on the PAS dataset (Supplementary Figure ), indicating the successful exploration of larger chemical space by O 2 -GEN. On the other hand, the GOR method of GaUDI treats rings as single tokens, which accelerates the convergence of the model, but it also limits the diversity of explored molecular structures, diminishing the novelty of the generated molecules.