22 citations · 23 across the 5 of their papers we have counts for
5 papers
Label-Conditioned Next-Frame Video Generation with Neural Flows
David Donahue
Recent state-of-the-art video generation systems employ Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs) to produce novel videos. However, VAE models typic…
Memory-Augmented Recurrent Networks for Dialogue Coherence
David Donahue, Yuanliang Meng, Anna Rumshisky
Recent dialogue approaches operate by reading each word in a conversation history, and aggregating accrued dialogue information into a single state. This fixed-size vector is not e…
Injecting Hierarchy with U-Net Transformers
David Donahue, Vladislav Lialin, Anna Rumshisky
The Transformer architecture has become increasingly popular over the past two years, owing to its impressive performance on a number of natural language processing (NLP) tasks. Ho…
Adversarial Text Generation Without Reinforcement Learning
David Donahue, Anna Rumshisky
Generative Adversarial Networks (GANs) have experienced a recent surge in popularity, performing competitively in a variety of tasks, especially in computer vision. However, GAN tr…
Adversarial Decomposition of Text Representation
Alexey Romanov, Anna Rumshisky, Anna Rogers +1
In this paper, we present a method for adversarial decomposition of text representation. This method can be used to decompose a representation of an input sentence into several ind…