Reproduce “Magnolia: A Persistent-Memory Agent Framework for Computational Chemistry” on OpenResearch

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About this paper

Tao Jiang, Benjamin Navet, Yousouf Taghzouti, Fabien Gandon, Louis-Félix Nothias, Élise Dumont

Magnolia carries project knowledge across computational-chemistry sessions by recording runs, turning observations into reviewable notes, and using relevant notes and human-approved rules later. In protein–peptide docking, researchers used this history to identify that better HADDOCK3 scores came from restraints targeting the wrong pocket. In a four-task replay, memory changed answers, though evidence was limited to one project.

Summary by alphaXiv.

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