arXiv — cs.AI preprintsInternational21 October 2026
AtomWorld-Mem: Memory-Restored World States for Long-Horizon Atomistic Evolution
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arXiv:2609.31133v3 Announce Type: replace Abstract: High-fidelity atomistic evolution over long timescales requires more than observing the current crystal configuration. Instantaneous atomistic snapshots are often incomplete: locally similar configurations can correspond to different hidden dynamical contexts, future event preferences, and waiting-time scales. We argue that this snapshot ambiguity makes long-horizon atomistic evolution fundamentally a memory-based world-state restoration problem. To address this, we introduce AtomWorld-Mem, a memory-restored atomistic world model that recover
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