10) by adding to it an entropy S of the probability distribution p (z = j | w, C w ): where: The hyper-parameter γ, which we further call entropy cost, controls the strength of the regularization and, in turn, the granularity of the learned sense representations.
γ > 0 encourages the model to learn more coarse-grained sense representations, whereas γ < 0 increases the granularity of the learned senses.