CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation
Generative modeling has emerged as a promising approach for crystal structure discovery. However, existing LLM-based generative models struggle with low-level atomic precision, while diffusion-based methods fall short in integrating high-level scientific knowledge. As a result, generated structures are often invalid, unstable, or do not possess desirable properties. To address this gap, we propose CrystalReasoner (CrysReas), an end-to-end LLM framework that generates crystal structures from natural language instructions through reasoning and alignment. CrysReas introduces physical priors as thinking tokens, which include crystallographic symmetry, local coordination environments and predi...
| Authors | Yuyang Wu, Stefano Falletta, Delia McGrath et al. |
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| Primary category | cs.AI |
| Published | 14 May 2026 |
| Last updated at source | 15 May 2026 |
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