Information Routing in Atomistic Foundation Models: How Task Alignment and Equivariance Shape Linear Disentanglement
What determines whether a molecular property prediction model organizes its representations so that geometric and compositional information can be cleanly separated? We introduce Compositional Probe Decomposition (CPD), which linearly projects out composition signal and measures how much geometric information remains accessible to a Ridge probe. We validate CPD with four independent checks, including a structural isomer benchmark where compositional projections score at chance while geometric residuals reach 94.6\% pairwise classification accuracy. Across ten models from five architectural families on QM9, we find a \emph{linear accessibility gradient}: models differ by $6.6\times$ in geo...
| Authors | Joshua Steier |
|---|---|
| Primary category | cs.LG |
| Published | 3 March 2026 |
| Last updated at source | 9 March 2026 |
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