AI RESEARCH
FlowMS: Flow Matching for De Novo Structure Elucidation from Mass Spectra
arXiv CS.LG
•
ArXi:2603.18397v1 Announce Type: new Mass spectrometry (MS) stands as a cornerstone analytical technique for molecular identification, yet de novo structure elucidation from spectra remains challenging due to the combinatorial complexity of chemical space and the inherent ambiguity of spectral fragmentation patterns. Recent deep learning approaches, including autoregressive sequence models, scaffold-based methods, and graph diffusion models, have made progress. However, diffusion-based generation for this task remains computationally demanding.