English(EN) CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials

大语言模型通过图文和空间推理模型推动材料科学发展

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-09 04:00

研究人员开发了用于材料科学应用的新型多模态大语言模型。其中一个模型 CatalyticMLLM，通过在单一框架内整合图和文本数据，统一了催化材料的性质预测和逆向设计。另一个模型 MOF-LLM，利用块级方法和专门的训练技术，增强了大语言模型在预测金属有机框架复杂结构方面的空间推理能力。 AI

影响这些模型展示了大语言模型在专业科学领域日益增长的能力，有望加速材料的发现和设计。

排序理由该集群包含两篇研究论文，详细介绍了用于材料科学应用的新型大语言模型架构。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.AI TIER_1 English(EN) · Yanjie Li, Jian Xu, Xu-Yao Zhang, Shiming Xiang, Nian Ran, Weijun Li, Cheng-Lin Liu · 2026-06-09 04:00

CatalyticMLLM：一种用于催化材料的图文多模态大语言模型

arXiv:2605.17254v3 Announce Type: replace Abstract: Property prediction and inverse structural design of catalytic materials are typically modeled as two independent tasks: the former predicts target properties from given structures, whereas the latter generates candidate structu…
arXiv cs.LG TIER_1 English(EN) · Mianzhi Pan, JianFei Li, Peishuo Liu, Botian Wang, Yawen Ouyang, Yiming Rong, Hao Zhou, Jianbing Zhang · 2026-06-09 04:00

增强大型语言模型在金属有机框架结构预测中的空间推理能力

arXiv:2601.09285v2 Announce Type: replace Abstract: Metal-organic frameworks (MOFs) are porous crystalline materials with broad applications such as carbon capture and drug delivery, yet accurately predicting their 3D structures remains a significant challenge. While Large Langua…