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arXiv AI By Pengfei Cai, Katharina S. C. J\"ager, Utkarsh Utkarsh, Nofit Segal, Bowen Deng, Akshay Subramanian, Rafael Gomez-Bombarelli

AtomSteer: Test-Time Constraint Steering for Atomistic Generative Models

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AtomSteer is a test‑time inference framework that steers pretrained atomistic generative models to satisfy structural constraints such as crystallographic symmetry, geometry, and stereochemistry. It applies bounded local projections, graph‑rigid stereochemical transformations, and periodic symmetry projections during sampling, accepting updates that improve constraint satisfaction while preserving the rest of the structure. The method is demonstrated on three backbones—FlowMM, ET‑Flow, and Boltz‑2—across tasks including de novo crystal generation, crystal structure prediction, molecular conformer generation, and protein‑ligand complex prediction, yielding improvements in space‑group coverage, stereochemical accuracy, and ligand E/Z error rates.

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