To that end, we define a backward LSTM that has a similar set of update equations except that only the first child will pass the hidden state to its parent.
the update equations are the same except that π(t) is replaced with κ(t), p(t) is replaced with s(t), and a different set of weight matrices and bias vectors are learned.