  We suggest a compositional vector representation of parse trees that relies
on a recursive combination of recurrent-neural network encoders. To demonstrate
its effectiveness, we use the representation as the backbone of a greedy,
bottom-up dependency parser, achieving state-of-the-art accuracies for English
and Chinese, without relying on external word embeddings. The parser's
implementation is available for download at the first author's webpage.
