335 citations · 1.7k across the 86 of their papers we have counts for
8 papers · 1 filter
Coupling Distributed and Symbolic Execution for Natural Language Queries
Lili Mou, Zhengdong Lu, Hang Li +1
Building neural networks to query a knowledge base (a table) with natural language is an emerging research topic in deep learning. An executor for table querying typically requires…
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…
StalemateBreaker: A Proactive Content-Introducing Approach to Automatic Human-Computer Conversation
Xiang Li, Lili Mou, Rui Yan +1
Existing open-domain human-computer conversation systems are typically passive: they either synthesize or retrieve a reply provided a human-issued utterance. It is generally presum…
How Transferable are Neural Networks in NLP Applications?
Lili Mou, Zhao Meng, Rui Yan +4
Transfer learning is aimed to make use of valuable knowledge in a source domain to help model performance in a target domain. It is particularly important to neural networks, which…
Backward and Forward Language Modeling for Constrained Sentence Generation
Lili Mou, Rui Yan, Ge Li +2
Recent language models, especially those based on recurrent neural networks (RNNs), make it possible to generate natural language from a learned probability. Language generation ha…
Improved Relation Classification by Deep Recurrent Neural Networks with Data Augmentation
Yan Xu, Ran Jia, Lili Mou +4
Nowadays, neural networks play an important role in the task of relation classification. By designing different neural architectures, researchers have improved the performance to a…