Authors
Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew M Dai, Rafal Jozefowicz, Samy Bengio
Publication date
2016
Conference
Proceedings of CoNLL
Description
Abstract: The standard unsupervised recurrent neural network language model (RNNLM)
generates sentences one word at a time and does not work from an explicit global
distributed sentence representation. In this work, we present an RNN-based variational
autoencoder language model that incorporates distributed latent representations of entire
sentences. This factorization allows it to explicitly model holistic properties of sentences
such as style, topic, and high-level syntactic features. Samples from the prior over these ...
Total citations
201614
Scholar articles
SR Bowman, L Vilnis, O Vinyals, AM Dai, R Jozefowicz… - arXiv preprint arXiv:1511.06349, 2015