unique molecular fragments of the 5,000 molecules generated for GSK3β+JNK3+QED+SA task for both FaST and MARS, and produce t-SNE visualization of these fragments in Figure and Figure . In total, we extracted 1.7k unique fragments from our model outputs vs only 1.1k unique fragments for Rational-RL and 500 unique fragments from MARS. The visualization shows that the fragments in the molecules generated by our model spans a much larger chemical space. This confirms the advantages of using a learned vocabulary, compared to using a fixed set of fragments, as we are able to utilize a much more diverse set of chemical subgraphs.