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cs.LG2026
Enhancing Spatial Reasoning in Large Language Models for Metal-Organic Frameworks Structure Prediction
Mianzhi Pan, JianFei Li, Peishuo Liu +5
Metal-organic frameworks (MOFs) are porous crystalline materials with broad applications such as carbon capture and drug delivery, yet accurately predicting their 3D structures rem…
cs.LG2025★ 2 cited
A Periodic Bayesian Flow for Material Generation
Hanlin Wu, Yuxuan Song, Jingjing Gong +6
Generative modeling of crystal data distribution is an important yet challenging task due to the unique periodic physical symmetry of crystals. Diffusion-based methods have shown e…
cs.LG2025
MoMa: A Modular Deep Learning Framework for Material Property Prediction
Botian Wang, Yawen Ouyang, Yaohui Li +8
Deep learning methods for material property prediction have been widely explored to advance materials discovery. However, the prevailing pre-train then fine-tune paradigm often fai…