where α and β are optimizable parameters and U ′ (R) is a temperature-independent pairwise potential represented by a spline function. Power-law function is selected here since it is a common non-linear model. The coarse-graining optimizations of these two types of potentials employ the same hyperparameters and simulation setups. Moreover, we have shown how a temperature-transferable CG model of PS melts can be developed using DiffCG. To achieve this, we harness the multi-objective optimization capabilities of DiffCG, utilizing target data collected from multiple thermodynamic states. In our approach, a dual-potential-like form is adopted to represent the pairwise potential within the transferable CG model. We conduct a systematic comparison between linear and non-linear T-dependent pairwise potentials to assess their effectiveness in ensuring temperature transferability. Our results indicate that the reproduction of both structural and thermodynamic properties in CG-PS models rely on the non-linear T-dependence of the pairwise potential.