Quantitatively, we evaluate the ability of the model to manipulate the given molecular property of molecules with the proposed strict success rate and relaxed success rate-L/G metrics (see Sec. 2). We evaluate the model's efficiency by comparing the training process of the linear models with a neural network-based predictor for a commonly used optimization-based method in terms of training/inference time, data, and number of oracle calls. Qualitatively, we visualize molecule manipulation including property distribution shift during manipulation, single and multiple property manipulations.