It enables simultaneous learning and estimation of multiple sequence labelings on the same input sequences, where time slices of the outputs of all the out sequences are regularly aligned.
it puts the distribution of states into Bayesian networks with cyclic dependencies, and exact inference is not tractable in such a model in general.