Furthermore, other frequently employed priors such as the Dirichlet distribution and the Dirichlet Process promote better generalising rule probability distributions based on externally set hyperparameter values, whose selection is frequently sensitive in terms of language pairs, or even the training corpus itself.
the CV-MLE prior aims for a data-driven Bayesian model, focusing on getting information from the data, instead of imposing external human knowledge on them (see also (Mackay and Petoy, 1995)).