In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful ...
Topic Model such as Latent Dirichlet Allocation(LDA) makes assumption that topic assignment of different words are conditionally independent. In this paper, we propose a new model...
We study the problem of summarizing DAG-structured topic hierarchies over a given set of documents. Example applications include automatically generating Wikipedia disambiguation ...
Ramakrishna Bairi, Rishabh K. Iyer, Ganesh Ramakri...
We propose a technique for learning representations of parser states in transitionbased dependency parsers. Our primary innovation is a new control structure for sequence-to-seque...
Chris Dyer, Miguel Ballesteros, Wang Ling, Austin ...
Training a high-accuracy dependency parser requires a large treebank. However, these are costly and time-consuming to build. We propose a learning method that needs less data, bas...