Performance metrics computed for the third and fourth-generation ML models. MAE is reported in eV for all models. The best R² and MAE for each property are in bold. The values are averaged over five-fold cross-validation models. The fourth-generation ML models include molecular descriptors concatenated to the MPNN output.

Property	3rd gen		4th gen
	R 2	MAE	R 2	MAE
HOMO	0.60 ± 0.01	0.796 ± 0.446	0.61 ± 0.01	0.330 ± 0.028
LUMO	0.76 ± 0.01	0.291 ± 0.044	0.76 ± 0.01	0.289 ± 0.028
H–L	0.47 ± 0.02	1.264 ± 0.696	0.50 ± 0.01	0.548 ± 0.029
VIE	0.86 ± 0.01	0.202 ± 0.043	0.86 ± 0.00	0.191 ± 0.024
AIE	0.87 ± 0.01	0.176 ± 0.015	0.87 ± 0.01	0.173 ± 0.006
CR1	0.37 ± 0.01	0.054 ± 0.001	0.38 ± 0.02	0.055 ± 0.002
CR2	0.40 ± 0.01	0.061 ± 0.001	0.44 ± 0.01	0.053 ± 0.001
HR	0.38 ± 0.02	0.126 ± 0.022	0.43 ± 0.02	0.133 ± 0.019
VEA	0.92 ± 0.01	0.193 ± 0.052	0.93 ± 0.00	0.157 ± 0.018
AEA	0.93 ± 0.01	0.160 ± 0.027	0.94 ± 0.01	0.154 ± 0.027
AR1	0.46 ± 0.02	0.057 ± 0.002	0.47 ± 0.02	0.051 ± 0.001
AR2	0.45 ± 0.01	0.048 ± 0.002	0.43 ± 0.02	0.052 ± 0.001
ER	0.50 ± 0.01	0.093 ± 0.002	0.50 ± 0.01	0.098 ± 0.006
S0S1	0.76 ± 0.01	0.252 ± 0.017	0.76 ± 0.01	0.249 ± 0.013
S0T1	0.87 ± 0.00	0.148 ± 0.012	0.87 ± 0.00	0.150 ± 0.028