Authors
Rafal Jozefowicz, Oriol Vinyals, Mike Schuster, Noam Shazeer, Yonghui Wu
Publication date
2016/2/7
Journal
arXiv preprint arXiv:1602.02410
Description
Abstract: In this work we explore recent advances in Recurrent Neural Networks for large
scale Language Modeling, a task central to language understanding. We extend current
models to deal with two key challenges present in this task: corpora and vocabulary sizes,
and complex, long term structure of language. We perform an exhaustive study on
techniques such as character Convolutional Neural Networks or Long-Short Term Memory,
on the One Billion Word Benchmark. Our best single model significantly improves state-of- ...
scale Language Modeling, a task central to language understanding. We extend current
models to deal with two key challenges present in this task: corpora and vocabulary sizes,
and complex, long term structure of language. We perform an exhaustive study on
techniques such as character Convolutional Neural Networks or Long-Short Term Memory,
on the One Billion Word Benchmark. Our best single model significantly improves state-of- ...
Total citations
Scholar articles
R Jozefowicz, O Vinyals, M Schuster, N Shazeer, Y Wu - arXiv preprint arXiv:1602.02410, 2016
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