Finally, an often overlooked aspect in the proper evaluation of de novo tools is the practical implementation of benchmarking, particularly when it involves retraining methods on the same data. To ensure optimal training conditions for each model, its training procedure may need to be adjusted for this particular data set, normally by re-running the hyperparameter search. Otherwise, the default hyperparameters proposed by the authors might turn out to be suboptimal, potentially leading to reduced performance and compromising the benchmarking results.