The article shows that using certain improper priors for model parameters can actually lead to well-defined Bayes factors, contrary to common belief. By introducing new ways to handle these priors, the researchers expanded the types of priors that can be used for model comparison. This includes popular shrinkage priors. The study demonstrates how to estimate Bayes factors for a specific type of model.