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English(EN) When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction

LLM在分子性质预测方面的评估，准确性和不确定性结果好坏参半

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员正在探索使用大型语言模型（LLM）进行分子性质预测，该领域以前由经典方法主导。一项评估七种前沿LLM的研究发现，虽然它们可以在有足够的上下文示例的情况下提高准确性，但它们自我报告的不确定性与预测误差仅有微弱的相关性。另一篇已被撤回的论文研究了分子性质预测中的上下文条件，强调了融合架构的显著影响，并揭示了标准基准测试实践中可能存在的缺陷，例如数据泄露。 AI

影响 这些研究突显了LLM在专业科学领域的潜力和局限性，为模型校准和稳健评估的未来研究指明了方向。

排序理由 该集群包含两篇学术论文，讨论了LLM在分子性质预测中的应用以及相关的基准测试挑战。

在 arXiv cs.LG 阅读 →

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LLM在分子性质预测方面的评估，准确性和不确定性结果好坏参半

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该集群包含两篇学术论文，讨论了LLM在分子性质预测中的应用以及相关的基准测试挑战。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Matthias Busch, Marius Tacke, Tamadur Albaraghtheh, Sviatlana V. Lamaka, Mikhail L. Zheludkevich, Roland C. Aydin, Christian Feiler, Christian J. Cyron ·

    Do LLMs Know When They Are Wrong About Molecules? In-Context Property Prediction with Self-Reported Uncertainty

    arXiv:2610.41745v1 Announce Type: new Abstract: Large language models (LLMs) are used in many domains, but molecular property prediction with them is still little explored. In this work we evaluate the capability of 7 frontier LLMs to predict molecular properties together with a …

  2. arXiv cs.LG TIER_1 English(EN) · Bryan Cheng, Jasper Zhang ·

    When Does Context Help? A Systematic Study of Target-Conditional Molecular Property Prediction

    arXiv:2604.06558v2 Announce Type: replace Abstract: We present the first systematic study of when target context helps molecular property prediction, evaluating context conditioning across 10 diverse protein families, 4 fusion architectures, data regimes spanning 67-9,409 trainin…

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