%0 Generic %1 vinyals2014grammar %A Vinyals, Oriol %A Kaiser, Lukasz %A Koo, Terry %A Petrov, Slav %A Sutskever, Ilya %A Hinton, Geoffrey %D 2014 %K nlp %T Grammar as a Foreign Language %U http://arxiv.org/abs/1412.7449 %X Syntactic constituency parsing is a fundamental problem in natural language processing and has been the subject of intensive research and engineering for decades. As a result, the most accurate parsers are domain specific, complex, and inefficient. In this paper we show that the domain agnostic attention-enhanced sequence-to-sequence model achieves state-of-the-art results on the most widely used syntactic constituency parsing dataset, when trained on a large synthetic corpus that was annotated using existing parsers. It also matches the performance of standard parsers when trained only on a small human-annotated dataset, which shows that this model is highly data-efficient, in contrast to sequence-to-sequence models without the attention mechanism. Our parser is also fast, processing over a hundred sentences per second with an unoptimized CPU implementation.

@misc{vinyals2014grammar, abstract = {Syntactic constituency parsing is a fundamental problem in natural language processing and has been the subject of intensive research and engineering for decades. As a result, the most accurate parsers are domain specific, complex, and inefficient. In this paper we show that the domain agnostic attention-enhanced sequence-to-sequence model achieves state-of-the-art results on the most widely used syntactic constituency parsing dataset, when trained on a large synthetic corpus that was annotated using existing parsers. It also matches the performance of standard parsers when trained only on a small human-annotated dataset, which shows that this model is highly data-efficient, in contrast to sequence-to-sequence models without the attention mechanism. Our parser is also fast, processing over a hundred sentences per second with an unoptimized CPU implementation.}, added-at = {2019-01-15T12:09:50.000+0100}, author = {Vinyals, Oriol and Kaiser, Lukasz and Koo, Terry and Petrov, Slav and Sutskever, Ilya and Hinton, Geoffrey}, biburl = {https://www.bibsonomy.org/bibtex/27520219e6dcc41d90551fa95b2818a0e/bechr7}, description = {Grammar as a Foreign Language}, interhash = {c5b0edb5edc545270318aeb86184fce7}, intrahash = {7520219e6dcc41d90551fa95b2818a0e}, keywords = {nlp}, note = {cite arxiv:1412.7449}, timestamp = {2019-01-15T12:09:50.000+0100}, title = {Grammar as a Foreign Language}, url = {http://arxiv.org/abs/1412.7449}, year = 2014 }