A recipe for scalable attention-based MLIPs: unlocking long-range accuracy with all-to-all node attention

Eric Qu, Brandon M. Wood, Aditi S. Krishnapriyan +1

Machine-learning interatomic potentials (MLIPs) have advanced rapidly, with many top models relying on strong physics-based inductive biases. However, as models scale to larger sys…