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English(EN) Language-Informed Flow Matching for Trend-Guided Structure-Based 3D Molecular Generation

AI利用语言引导晶体和分子结构生成

两篇新研究论文介绍了使用语言信息流匹配进行结构生成的新方法。第一篇TFMat使用结构化文本引导晶体结构生成,提高了匹配率和与期望属性的一致性。第二篇LiFT采用语言衍生的化学先验知识来指导用于药物设计的3D分子生成,在保持结构有效性的同时提高了药物化学指标。 AI

影响 这些方法通过实现由人类语言引导的更精确、更高效的复杂结构生成,有望加速材料科学和药物发现。

排序理由 两篇在arXiv上发表的学术论文,介绍了结构生成的新方法。

在 arXiv cs.LG 阅读 →

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

AI利用语言引导晶体和分子结构生成

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两篇在arXiv上发表的学术论文,介绍了结构生成的新方法。
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2 independent sources
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Wentao Li ·

    文本引导的流匹配实现样本高效的晶体结构生成

    arXiv:2609.01076v1 Announce Type: cross Abstract: Crystal generators can now propose periodic structures, but their control interfaces remain poorly matched to the mixed descriptors used in materials design. Text provides a compact way to combine composition, symmetry, prototype …

  2. arXiv cs.LG TIER_1 English(EN) · Tianyu Gao, Zhikai Su, Jiashu Li, Wenjun Gao, Zichuan Ying, Zhe Zhao, Fei Zhang, Ye Wei ·

    面向趋势引导的结构化三维分子生成的语言信息流匹配

    arXiv:2608.31009v1 Announce Type: new Abstract: Structure-based drug design (SBDD) requires ligands that satisfy both 3D target affinity and 1D chemical validity. Existing controllable generation methods often rely on task-specific fine-tuning or externally imposed sampling-time …