The sampled 2D-grid for the molecules in XALKENEDB covers the configurational space of interest, i.e., the region around the S 1 /S 0 -conical intersection. Typically, conical intersection-geometries with δ(HC = CH) between 80 and 100 • and r(C = C) ranging from 2.5 to 2.8 Bohr are observed for alkenes. This is supported by the hopping The error-difference plots for the alkenes show that PaiNN-based SpaiNN models outperform their SchNet-based counterparts in the relevant regions of chemical configuration space for all three alkenes (cf. green vs. pink color in Figure ). While the training data encompasses δ(HC = CH) values ranging from 0 to 180 • , mirroring the 2D-grid reference points, the C = C double bonds cover distances approximately from 2.25 to 2.80 Bohr in the train-ing set. Consequently, the models interpolate with respect to angles but extrapolate along the distance axis. Nevertheless, it is apparent that SpaiNN models utilizing PaiNN representation exhibit superior generalization in regions typically associated with S 1 /S 0 conical intersections. These intersections, marked by black symbols in Figure , are obtained from SHARC simulations (note: while geometries may not align precisely on the grid, corresponding C = C bond distances and dihedrals are utilized for plotting).