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.
@article{arxiv.1603.00375,
title = {Easy-First Dependency Parsing with Hierarchical Tree LSTMs},
author = {Eliyahu Kiperwasser and Yoav Goldberg},
journal= {arXiv preprint arXiv:1603.00375},
year = {2018}
}