(2017) induce richer internal structure by imposing structural constraints on the probability distribution computed by the attention mechanism.
they normalize f ij with a projective dependency tree using the inside-outside algorithm (Baker, 1979): This process is differentiable, so the model can be trained end-to-end and learn structural information without relying on a parser.