English(EN) CoMPASS: Collaborative Molecular Property Prediction via Adaptive Small-Large Model Synergy

新AI框架融合小型和大型模型用于分子预测

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-01 04:00

研究人员开发了CoMPASS，一个新颖的框架，它协同小型和大型AI模型进行分子属性预测。该系统使用图注意力网络作为其主要预测器，检索相关分子来告知大型语言模型。然后，LLM的输出被转换为对主要模型的有界校正，在不影响高置信度预测的情况下提高不确定区域的准确性。这种协作方法表明，生成式推理可以通过受控校正有效地增强校准预测。 AI

影响该框架可以提高AI在科学研究中的准确性和可靠性，特别是在药物发现和材料科学领域。

排序理由该集群包含一篇详细介绍用于分子属性预测的新AI框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Wentao Li, Jiangjie Qiu, Yijun Li, Leyi Zhao, Xiaonan Wang · 2026-09-01 04:00

CoMPASS：通过自适应大小模型协同进行分子性质的协同预测

arXiv:2608.30674v1 Announce Type: cross Abstract: Accurate molecular property prediction requires both statistical reliability and chemical reasoning. Graph neural networks can be calibrated directly on labeled assays but remain limited by the coverage of their training data. Lar…

本文如何被排名

报道来源 [1]

CoMPASS：通过自适应大小模型协同进行分子性质的协同预测

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