Fine-tuning ML interatomic potentials via a new LoRA-based Equitrain framework with minimal additional data improves phonon and thermal predictions over base and scratch-trained models in 53 systems.
From Ultrasoft Pseudopotentials to the Projector Augmented- Wave Method
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
cond-mat.mtrl-sci 1years
2026 1verdicts
UNVERDICTED 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
Parameter-Efficient Fine-Tuning of Machine-Learning Interatomic Potentials for Phonon and Thermal Properties
Fine-tuning ML interatomic potentials via a new LoRA-based Equitrain framework with minimal additional data improves phonon and thermal predictions over base and scratch-trained models in 53 systems.