%0 Generic %1 andor2016globally %A Andor, Daniel %A Alberti, Chris %A Weiss, David %A Severyn, Aliaksei %A Presta, Alessandro %A Ganchev, Kuzman %A Petrov, Slav %A Collins, Michael %D 2016 %K nlp nn parsing %T Globally Normalized Transition-Based Neural Networks %U http://arxiv.org/abs/1603.06042 %X We introduce a globally normalized transition-based neural network model that achieves state-of-the-art part-of-speech tagging, dependency parsing and sentence compression results. Our model is a simple feed-forward neural network that operates on a task-specific transition system, yet achieves comparable or better accuracies than recurrent models. We discuss the importance of global as opposed to local normalization: a key insight is that the label bias problem implies that globally normalized models can be strictly more expressive than locally normalized models.

@misc{andor2016globally, abstract = {We introduce a globally normalized transition-based neural network model that achieves state-of-the-art part-of-speech tagging, dependency parsing and sentence compression results. Our model is a simple feed-forward neural network that operates on a task-specific transition system, yet achieves comparable or better accuracies than recurrent models. We discuss the importance of global as opposed to local normalization: a key insight is that the label bias problem implies that globally normalized models can be strictly more expressive than locally normalized models.}, added-at = {2016-09-21T04:29:36.000+0200}, author = {Andor, Daniel and Alberti, Chris and Weiss, David and Severyn, Aliaksei and Presta, Alessandro and Ganchev, Kuzman and Petrov, Slav and Collins, Michael}, biburl = {https://www.bibsonomy.org/bibtex/21103a5277b755925bfcf9f99bcb089ff/jkan}, interhash = {db3b21284fce9df6e23b83c53c0fcb4b}, intrahash = {1103a5277b755925bfcf9f99bcb089ff}, keywords = {nlp nn parsing}, note = {cite arxiv:1603.06042}, timestamp = {2016-09-21T04:29:36.000+0200}, title = {Globally Normalized Transition-Based Neural Networks}, url = {http://arxiv.org/abs/1603.06042}, year = 2016 }