97 citations · 220 across the 3 of their papers we have counts for
3 papers · 1 filter
On Accurate Evaluation of GANs for Language Generation
Stanislau Semeniuta, Aliaksei Severyn, Sylvain Gelly
Generative Adversarial Networks (GANs) are a promising approach to language generation. The latest works introducing novel GAN models for language generation use n-gram based metri…
A Hybrid Convolutional Variational Autoencoder for Text Generation
Stanislau Semeniuta, Aliaksei Severyn, Erhardt Barth
In this paper we explore the effect of architectural choices on learning a Variational Autoencoder (VAE) for text generation. In contrast to the previously introduced VAE model for…
Recurrent Dropout without Memory Loss
Stanislau Semeniuta, Aliaksei Severyn, Erhardt Barth
This paper presents a novel approach to recurrent neural network (RNN) regularization. Differently from the widely adopted dropout method, which is applied to \textit{forward} conn…