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StableReported 2026-10-02 12:00

ReLaG: A Scalable Framework Generalizing Random Splits to Data with Latent Relations

ReLaG is a new framework that addresses the issue of non-independent train-test splits in datasets with related samples, such as biochemical studies, by modeling sample relatedness and producing independent subsets.

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Evidence

  • AarXiv cs.LGInstitution2026-10-02 12:00
    > Abstract: Random splitting can yield non-independent train--test subsets when a dataset contains related samples, as is common in certain applications such a…
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  • AarXiv cs.LGInstitution2026-10-02 12:00
    Abstract: Random splitting can yield non-independent train--test subsets when a dataset contains related samples, as is common in certain applications such as…
    View source