[
    {
        "id": "osp-21376",
        "type": "article-journal",
        "title": "Nearest-neighbour baselines for fingerprint prediction from MS/MS spectra under different assumptions",
        "author": [
            {
                "family": "Khoo",
                "given": "Ling Min Serena"
            }
        ],
        "URL": "https://omanscience.com/ar/articles/nearest-neighbour-baselines-for-fingerprint-prediction-from-ms-ms-spectra-under-different-assumptions",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "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."
    }
]