1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2020
Generating Descriptions for Sequential Images with Local-Object Attention and Global Semantic Context Modelling
Jing Su, Chenghua Lin, Mian Zhou +2
In this paper, we propose an end-to-end CNN-LSTM model for generating descriptions for sequential images with a local-object attention mechanism. To generate coherent descriptions,…
cs.CL2020★ 1 cited
Improving Variational Autoencoder for Text Modelling with Timestep-Wise Regularisation
Ruizhe Li, Xiao Li, Guanyi Chen +1
The Variational Autoencoder (VAE) is a popular and powerful model applied to text modelling to generate diverse sentences. However, an issue known as posterior collapse (or KL loss…
cs.CL2020★ 1 cited
DGST: a Dual-Generator Network for Text Style Transfer
Xiao Li, Guanyi Chen, Chenghua Lin +1
We propose DGST, a novel and simple Dual-Generator network architecture for text Style Transfer. Our model employs two generators only, and does not rely on any discriminators or p…