English(EN) MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion

新方法通过感知角色的扩散优化分子图生成

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-27 04:00

研究人员开发了MotifRole-Diff，一种用于掩码离散扩散生成分子图的新方法。该方法通过根据分子图标记的角色在去噪难度和对最终分子的影响，为其分配不同的掩码率来优化掩码计划。该策略旨在提高重建准确性和生成分子的质量。 AI

影响改进了分子图生成技术，可能导致更准确、更高效的药物发现或材料科学应用。

排序理由详细介绍分子图生成新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Tasfia Nuzhat Ornee, Elias Hossain, Ivan Garibay, Niloofar Yousef · 2026-07-27 04:00

MotifRole-Diff: 面向掩码分子图扩散的风险最优角色感知腐蚀

arXiv:2607.21634v1 Announce Type: new Abstract: Masked discrete diffusion for molecular graph generation typically applies a uniform corruption schedule to all tokens in a lossless graph-to-sequence representation, implicitly treating structurally heterogeneous molecular componen…