CrystalREPA closes the representation gap between crystal generators and universal MLIPs via contrastive alignment, yielding more stable and valid generated crystals while revealing that MLIP teacher quality is better predicted by representation distinguishability than by leaderboard accuracy.
Graph atomic cluster expansion for semilocal interactions beyond equivariant message passing.Physical Review X, 14(2):021036
2 Pith papers cite this work. Polarity classification is still indexing.
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cond-mat.mtrl-sci 2years
2026 2verdicts
UNVERDICTED 2roles
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An equivariant message-passing neural network embeds atomic spins explicitly to learn magnetic interactions, achieving near-DFT accuracy and data efficiency across magnetic systems via fine-tuning.
citing papers explorer
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CrystalREPA: Transferring Physical Priors from Universal MLIPs to Crystal Generative Models
CrystalREPA closes the representation gap between crystal generators and universal MLIPs via contrastive alignment, yielding more stable and valid generated crystals while revealing that MLIP teacher quality is better predicted by representation distinguishability than by leaderboard accuracy.
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Equivariant Many-body Message Passing Interatomic Potentials for Magnetic Materials
An equivariant message-passing neural network embeds atomic spins explicitly to learn magnetic interactions, achieving near-DFT accuracy and data efficiency across magnetic systems via fine-tuning.