Given the pretrained coupled Graphormer, we further learn our HGAR model via a multi-task fine-tuning step. For each product Gp = (A, B), we have the following label information: i) a one-hot 4 indicating the bond type of the reaction center, iii) a binary scalar y t u * ∈ {0, 1} indicating whether the synthon Gs is completed, and iv) a one-hot vector y m ∈ {0, 1} |X | indicating the type of the motif added to the synthon. Based on the labeled data, we consider the four prediction tasks shown in Section 3.