63 citations · 90 across the 6 of their papers we have counts for
4 papers · 1 filter
Search and Learn: Improving Semantic Coverage for Data-to-Text Generation
Shailza Jolly, Zi Xuan Zhang, Andreas Dengel +1
Data-to-text generation systems aim to generate text descriptions based on input data (often represented in the tabular form). A typical system uses huge training samples for learn…
Dialogue Session Segmentation by Embedding-Enhanced TextTiling
Yiping Song, Lili Mou, Rui Yan +4
In human-computer conversation systems, the context of a user-issued utterance is particularly important because it provides useful background information of the conversation. Howe…
Compressing Neural Language Models by Sparse Word Representations
Yunchuan Chen, Lili Mou, Yan Xu +2
Neural networks are among the state-of-the-art techniques for language modeling. Existing neural language models typically map discrete words to distributed, dense vector represent…
Sequence to Backward and Forward Sequences: A Content-Introducing Approach to Generative Short-Text Conversation
Lili Mou, Yiping Song, Rui Yan +3
Using neural networks to generate replies in human-computer dialogue systems is attracting increasing attention over the past few years. However, the performance is not satisfactor…