First, we examine the effectiveness of DiffCG with various multi-objective optimization algorithms in the construction of CG models of PS melts at a single thermodynamic state, i.e., temperature T = 600 K and pressure P = 1 atm. The total mean square error (MSE) defined as: E total = ϵ bond + ϵ angle + ϵ dihedral + ϵ RDF + ϵ pressure as a function of iterations during the optimization process using various multi-objective optimization algorithms is shown in Figure . Among all these algorithms, the CoV algorithm achieves the best performance in terms of minimizing E total . Surprisingly, the Auxiliary method even behaves worse than the uniform one, although its error minimization is stable than others. dicating its advantages over other multi-objective algorithms in structural coarse-graining.