Figure shows attributions from both models for a subset of accurately predicted compounds in the selected group. Note that magenta atom contributions are sites which push the prediction towards lower values of logD (i.e., less lipophilic), and green contributions indicate sites that push the predictions towards higher values of logD (i.e., more lipophilic). We observe that the attributions produced by the base model are uniformly green for all compounds, which is not useful to a chemist trying to find optimal positions for modifications. This is the case for all compounds of the cluster, not only for those shown in Figure . Furthermore, the atom contributions according to the XAI model are more diverse and sparse: there are atom contributions labeled as (i) increasing lipophilicity, (ii) decreasing lipophilicity and (iii) as largely irrelevant to the prediction. Both models give similar predictions. In four out of six cases, the XAI model attributes lower lipophilicity to the ester group. Similarly, the heteroatoms in the three rings of the scaffold are often marked as lowering the lipophilicity, or at least are excluded from the green highlights. Both of which accords with a medicinal chemist's intuition. Nevertheless, the attributions are not perfect, especially from a stability point of view: some very similar compounds have different attributions in the XAI model (for example, molecules 239 and 621 only differ by one methyl group but have very different explanations).