Nearest-neighbour baselines for fingerprint prediction from MS/MS spectra under different assumptions

Abstract:It has recently been shown that nearest-neighbour retrieval provides a strong baseline for molecular fingerprint prediction from MS/MS spectra, with several variants matching or outperforming current deep learning models (Khoo and Barzilay, 2026; Liu et al., 2026; Gupta et al., 2026). Importantly, "nearest neighbour" encompasses a family of retrieval methods that differ in the information assumed to be available at inference. In this report, we systematically compare several nearest-neighbour variants and show how these differing assumptions affect performance. Our goal is to establish stricter baselines that enable more rigorous benchmarking and better measure progress in this area.

Machine Learning (cs.LG); Computational Engineering, Finance, and Science (cs.CE); Machine Learning (stat.ML)

arXiv:2610.02249 [cs.LG]

(or arXiv:2610.02249v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2610.02249 Focus to learn more arXiv-issued DOI via DataCite

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