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.