Xiao-Qing Liu

Foundation-Model Supervision of Distilled Potentials for Million-Atom Molecular Dynamics

Machine-learned interatomic potentials distilled from foundation models enable fast large-scale molecular dynamics (MD), but they can fail locally in chemical environments that their training data did not sample. System-averaged error metrics and small random audits often miss such sparse or isolated failures. Here we...