English(EN) Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling

语言大模型在小分子药物发现中展现潜力

作者 PulseAugur 编辑部 · [2 个来源] · 2026-09-07 04:00

研究人员正在探索使用语言大模型（LLMs）进行药物发现中的小分子设计。一种方法是在合成任务上训练语言大模型，这些任务可以泛化到复杂分子优化问题，并有望超越更大的模型。另一种方法是将语言大模型与进化算法相结合，在分子优化基准测试中取得新的最先进成果，尤其是在多属性优化场景中。 AI

影响这些方法可以通过提高设计具有期望属性的分子的效率和有效性来加速药物发现。

排序理由该集群包含两篇在arXiv上发表的学术论文，详细介绍了在分子设计和优化中使用语言大模型的 novel 方法。

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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Newsworthiness bucket: Research; 该集群包含两篇在arXiv上发表的学术论文，详细介绍了在分子设计和优化中使用语言大模型的 novel 方法。
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arXiv cs.LG TIER_1 English(EN) · Frank Hu, Shriram Chennakesavalu, Zichen Wang, Patricia Suriana, Bodhi Vani, Kirill Shmilovich, Kangway Chuang, Colin Grambow · 2026-09-07 04:00

使用合成任务扩展训练用于小分子设计的语言大模型

arXiv:2609.04735v1 Announce Type: new Abstract: Designing viable drug candidates requires searching a combinatorially large and rugged chemical space for molecules that satisfy multiple, often competing, objectives. Large language models (LLMs) provide a useful generative prior f…
arXiv cs.LG TIER_1 English(EN) · Philipp Guevorguian, Menua Bedrosian, Tigran Fahradyan, Gayane Chilingaryan, Armen Aghajanyan, Hrant Khachatrian · 2026-09-07 04:00

使用大型语言模型优化小分子

arXiv:2407.18897v2 Announce Type: replace Abstract: Molecular optimization, the process of designing molecules with desirable properties, represents a critical challenge in drug discovery. Recent advancements in large language models (LLMs) have opened new opportunities for their…