ARK: Angular Relational Knowledge Distillation

March 3, 2026 ยท View on GitHub

This repository contains the implementation used in:

Angular relational knowledge distillation of machine learning interatomic potentials for scalable catalyst exploration

ARK distills relational physics from a large teacher MLIP into a compact student by aligning edge-level relational vectors with a contrastive objective.

Model configurations and benchmark results

Model configurations

Compression ratio denotes the parameter reduction from teacher to student.

DomainDatasetTeacherStudentCompression
CatalysisOC20EquiformerV2 (153M)EquiformerV2 (22M)7.0x
MaterialsOMat24EquiformerV2 (153M)EquiformerV2 (22M)7.0x
MoleculesSPICEMACE-OFF Large (4.7M)GemNet-dT (0.67M)7.0x

Distillation results

ARK uses n2n loss for OC20 and OMat24, and n2n + Hessian loss for SPICE.
Hessian distillation was not applied to OMat24.
Best student results are in bold.

Training strategyOC20 O* EnergyOC20 O* ForceOC20 200K EnergyOC20 200K ForceOMat24 Rattled-1000 EnergyOMat24 Rattled-1000 ForceOMat24 Rattled-1000 StressSPICE Monomers EnergySPICE Monomers ForceSPICE Solvated AA EnergySPICE Solvated AA ForceSPICE Iodine EnergySPICE Iodine Force
Teacher39.85.8171.512.49.756.33.40.656.61.319.41.315.3
Undistilled294.55.9474.951.818.192.54.12.213.41.722.93.225.4
n2n252.95.8412.834.817.588.64.12.314.51.521.43.025.9
HessianOOMOOMOOMOOMOOMOOMOOM1.28.50.411.42.419.6
ARK231.75.8371.134.116.383.04.01.48.90.411.92.219.4

All entries are Mean Absolute Error (MAE) unless otherwise noted.
OC20 energy units: meV.
OMat24 and SPICE energy units: meV/atom.
Force units: meV/A.
Stress units: meV/A^3.

Experiments

Experimental details are described in the README.md files of each subfolder: OC20, OMat_and_HTS, and SPICE.

Acknowledgement

This repository builds on: