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The results suggest that integrating persistent execution with session-level provenance can improve the reliability of AI-assisted scientific workflows, and recommend that integrating persistent execution with session-level provenance can improve the reliability of AI-assisted scientific workflows.
Determining molecular structures from spectroscopic data remains fundamentally challenging because the inverse problem is intrinsically underdetermined: individual spectra are sparse, low-dimensional, and encode only partial structural evidence relative to the vast space of possible molecules. We address this challenge...
HME is presented, a framework that combines multiple views of molecules to improve molecular understanding and design and enables bidirectional navigation of the chemical-linguistic space, achieving consistent improvements across molecular comprehension and design tasks over strong baselines.
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