For this study, it is essential to use a dataset with a significant portion of resonance-exhibiting molecules to avoid conducting a mere ablation test of atom and bond features. We selected a subset of the QuantumPioneer 28 (QP) dataset generated in-house, which includes a large number of resonance-exhibiting radicals as well as closed-shell molecules. QP is among the largest and most diverse open-source quantum chemistry databases, containing over 350,000 small organic molecules with up to 21 heavy atoms, including elements like H, C, N, O, F, Si, P, S, Cl, Br, and I. The QP dataset provides molecular geometries and vibrational frequencies optimized at the ω-B97X-D/def2-SVP level of theory and single-point energies calculated at the DLPNO-CCSD(T)-F12a/def2-TZVP level of theory. The dataset also includes thermodynamic properties, such as enthalpies of formation, that are derived via advanced atom-energy and bond-additivity correction schemes. For our analysis, we sampled 50,000 molecules, limiting our selection to those containing only H, C, N, and O atoms. Canonicalized SMILES were used to ensure that each molecule has a unique SMILES representation. For species with equivalent resonance structures, such as benzene, canonicalized SMILES provide a single representation, effectively imposing a resonance invariant representation in these systems. For the target property, we selected standard heat of formation (∆H • f ). The distribution of different species in the final dataset is shown in Table .