23 citations · 157 across the 46 of their papers we have counts for
6 papers · 1 filter
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,…
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…
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…
A Text Reassembling Approach to Natural Language Generation
Xiao Li, Kees van Deemter, Chenghua Lin
Recent years have seen a number of proposals for performing Natural Language Generation (NLG) based in large part on statistical techniques. Despite having many attractive features…
Fast and Scalable Dialogue State Tracking with Explicit Modular Decomposition
Dingmin Wang, Chenghua Lin, Qi Liu +1
We present a fast and scalable architecture called Explicit Modular Decomposition (EMD), in which we incorporate both classification-based and extraction-based methods and design f…
Understanding Linearity of Cross-Lingual Word Embedding Mappings
Xutan Peng, Mark Stevenson, Chenghua Lin +1
The technique of Cross-Lingual Word Embedding (CLWE) plays a fundamental role in tackling Natural Language Processing challenges for low-resource languages. Its dominant approaches…