526 citations · 1.1k across the 32 of their papers we have counts for
4 papers · 1 filter
Arc-Standard Spinal Parsing with Stack-LSTMs
Miguel Ballesteros, Xavier Carreras
We present a neural transition-based parser for spinal trees, a dependency representation of constituent trees. The parser uses Stack-LSTMs that compose constituent nodes with depe…
AMR Parsing using Stack-LSTMs
Miguel Ballesteros, Yaser Al-Onaizan
We present a transition-based AMR parser that directly generates AMR parses from plain text. We use Stack-LSTMs to represent our parser state and make decisions greedily. In our ex…
Are Emojis Predictable?
Francesco Barbieri, Miguel Ballesteros, Horacio Saggion
Emojis are ideograms which are naturally combined with plain text to visually complement or condense the meaning of a message. Despite being widely used in social media, their unde…
DyNet: The Dynamic Neural Network Toolkit
Graham Neubig, Chris Dyer, Yoav Goldberg +22
We describe DyNet, a toolkit for implementing neural network models based on dynamic declaration of network structure. In the static declaration strategy that is used in toolkits l…