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English(EN) BiMol-Diff: A Unified Diffusion Framework for Molecular Generation and Captioning

BiMol-Diff框架通过感知token的扩散统一分子生成和描述

作者 PulseAugur 编辑部 · [3 个来源] ·

研究人员推出BiMol-Diff，一个新颖的扩散框架，旨在连接分子结构和自然语言以实现可控设计。该方法利用了感知token的噪声调度，根据token恢复难度调整损坏级别，以更好地保留关键子结构。BiMol-Diff在分子重建方面表现出改进，在基准数据集上实现了15.4%的精确匹配相对提升，并在分子描述任务中也展现出强劲性能。 AI

影响 引入了一种新的分子结构-语言建模方法，可能改进AI驱动的药物发现和设计。

排序理由 介绍用于分子生成和描述的新框架的学术论文。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 3 个来源。 我们如何撰写摘要 →

BiMol-Diff框架通过感知token的扩散统一分子生成和描述

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报道来源 [3]

  1. arXiv cs.CL TIER_1 English(EN) · Aditya Hemant Shahane, Anuj Kumar Sirohi, Devansh Arora, Nitin Kumar, Prathosh A P, Sandeep Kumar ·

    BiMol-Diff：用于分子生成和描述的统一扩散框架

    arXiv:2604.24089v1 Announce Type: new Abstract: Bridging molecular structures and natural language is essential for controllable design. Autoregressive models struggle with long-range dependencies, while standard diffusion processes apply uniform corruption across positions, whic…

  2. arXiv cs.CL TIER_1 English(EN) · Sandeep Kumar ·

    BiMol-Diff：用于分子生成和描述的统一扩散框架

    Bridging molecular structures and natural language is essential for controllable design. Autoregressive models struggle with long-range dependencies, while standard diffusion processes apply uniform corruption across positions, which can distort structurally informative tokens. W…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    BiMol-Diff：用于分子生成和描述的统一扩散框架

    Bridging molecular structures and natural language is essential for controllable design. Autoregressive models struggle with long-range dependencies, while standard diffusion processes apply uniform corruption across positions, which can distort structurally informative tokens. W…

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