Despiting the linear structured left-branching and rightbranching tree encoders, we find that, tree-based encoders generally perform better than Bi-LSTMs on tasks of sentence relation and sentence generation, which may require relatively more long term context features for obtaining better performances.
as desired, on shortsentence groups, the performance gap between Bi-LSTM and binary balanced tree LSTM is not obvious, while it grows with the test sentences turning longer.