Five distinct CG models were parameterized for each system and CG mapping: IBI (SP), IBI with pressure correction (SP PC ), DeePCG (ML), a ∆-model based on a combination of IBI and DeePCG (T L) and a ∆-model based on a combination of IBI with pressure-correction and DeePCG (T L PC ). These models were benchmarked in reproducing on-target properties that were seen during training, including RDF and pressure, and off-target properties that were not directly trained on, including molecular enthalpy of vaporization (H v ) and self-diffusion coefficient. The rationale behind these comparisons is that on-target properties are expected to be better reproduced by complex models (i.e., the ML and the TL models) while the accuracy of off-target properties is diagnostic of overfitting and may be better reproduced by simpler models. All reported errors are normalized with respect to the atomistic values. The procedure for simulations performed to evaluate these errors as well as the error expressions used are described in Section S5.