MSAlign aligns frozen DreaMS and ChemBERTa models with MLPs and candidate-based contrastive learning to outperform prior methods on molecule retrieval from MS/MS spectra while quantifying distribution shift in data splits.
expert” models, which can be selected at inference time when the adduct is known. In Table 9 we report the results of these different strategies. In the
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MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification
MSAlign aligns frozen DreaMS and ChemBERTa models with MLPs and candidate-based contrastive learning to outperform prior methods on molecule retrieval from MS/MS spectra while quantifying distribution shift in data splits.