These methods hold the promise of enabling molecular dynamics simulations on a highly accurate potential energy surface, possibly matching the accuracy of high-level quantum chemistry, and even allow for extensions to excited state dynamics . However, any machine learning potential can only be as good as the quantum-chemical reference data on which it has been trained. This includes not only the underlying quantum-chemical methods, but also the accuracy of the fragmentation scheme.