Large-scale conformational rearrangements in molecules can be represented by changes in torsion angles (dihedrals), which correspond to rotations occurring around flexible bonds. For example, the structures of biomolecules such as proteins or RNA are compared and analyzed in terms of such angles, using the Ramachandran plot and probabilistic models of local structure as prominent examples. Transitions between different conformations usually account for the slowest processes in simulations. Therefore, generating representative ensembles of torsions is time-consuming and challenging. For this reason, models focusing on torsion angles are useful means to conformational sampling. Recent work encoding conformations in small molecules using torsions include GeoMol , Torsional Diffusion , Tora3D , and VonMisesNet . Apart from capturing major conformational changes, torsion angles are attractive as they reduce the dimensionality of conformational space and are intrinsically invariant to rigid body symmetries. However, even if some of these methods have been adapted to generate equilibrium samples, they still cannot model stochastic fluctuations in the local structure, and their evaluation as surrogates of the Boltzmann distribution is limited.