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News/Training seeds and model-selection stability in recommender-system evaluation
arxiv
PublishedSeptember 3, 2026 at 4:00 AM

Training seeds and model-selection stability in recommender-system evaluation

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Publisher summary· verbatim

arXiv:2609.02499v1 Announce Type: cross Abstract: Recommender-system experiments often rely on a single random training seed, assuming that run-to-run stochasticity has limited impact on evaluation conclusions. This assumption is risky, as a training seed may influence several algorithm-dependent me

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