English(EN) MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts

MolReFlect框架对齐分子和文本，以增强LLM的理解能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-29 04:00

研究人员开发了MolReFlect，一个新颖的师生框架，旨在改善分子结构与文本描述之间的对齐。该方法使大型语言模型能够学习特定分子亚结构与描述它们的短语之间的细粒度对应关系，从而提高分子相关任务的准确性和可解释性。MolReFlect旨在克服先前将分子视为整体处理方法的局限性，实验结果表明，它在分子-标题翻译方面取得了最先进的性能。 AI

影响通过改善分子-文本理解能力，增强了LLM在药物发现和材料科学等科学领域的应用能力。

排序理由这是一篇研究论文，详细介绍了使用LLM对齐分子和文本的新框架。

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Jiatong Li, Yunqing Liu, Wei Liu, Jingdi Le, Di Zhang, Wenqi Fan, Dongzhan Zhou, Yuqiang Li, Qing Li · 2026-04-29 04:00

MolReFlect：迈向分子与文本的上下文细粒度对齐

arXiv:2411.14721v2 Announce Type: replace Abstract: Molecule discovery is a pivotal research field, impacting everything from medicine to materials. Recently, Large Language Models (LLMs) have been widely adopted in molecular understanding and generation, serving as a bridge betw…

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报道来源 [1]

MolReFlect：迈向分子与文本的上下文细粒度对齐

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