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statistical-guarantees

topic1 events
papersSEP 11 04:00 UTC

arXiv paper proposes statistical guarantees for post-training hyperparameter selection

A new arXiv preprint addresses how to choose hyperparameters after a model has already been trained, such as inference-time settings and implementation-level options. The work aims to move this process beyond ad hoc tuning by providing statistical validity guarantees for the selected configuration. It targets deployment scenarios where pre-trained models still have multiple degrees of freedom that need to be fixed.

research/hyperparameters/post-training/statistics