For correlation energy data, the same eight small closed-shell atoms/ions (H -, He, Be, Mg, Ne, Ar, Ca, and Kr) as for ML2 are employed. Additionally, the following collection of 13 small closed-shell complexes from the MB16-43 database 11 is incorporated: Cl 2 , BeH 2 , NaH, H 2 , BH 3 , AlH 3 , MgH 2 , N 2 , SiH 4 , LiH, F 2 , CH 4 and P 2 . Here, we calculate the reference correlation energies in PySCF using CCSD(T) level of theory with the def2-QZVP basis set for structures taken from the original dataset. We further train the MLS2 model on correlation energy data points from H 2 (calculated at FCI/def2-QZVPPD level of theory), N 2 (taken from Ref. They are visualized, for instance, as cross-marked points in Fig. . We also plot the HF, MP2, and κMP2 based results for comparison in Figs. and respectively. The MP2 correlation energies diverge at large interatomic distances due to the singularity coming from a small orbital energy gap, which explains the physically wrong magenta dissociation curves. Regularization removes divergence and captures the correct physics when stretching the bond. Adding the training data points at large distances helps MLS2 to efficiently bridge the gap between regularized PT2 and true correlation energies.