14 citations · 33 across the 5 of their papers we have counts for
6 papers
An Empirical Study on Neural Keyphrase Generation
Rui Meng, Xingdi Yuan, Tong Wang +3
Recent years have seen a flourishing of neural keyphrase generation (KPG) works, including the release of several large-scale datasets and a host of new models to tackle them. Mode…
Diversifying Dialogue Generation with Non-Conversational Text
Hui Su, Xiaoyu Shen, Sanqiang Zhao +5
Neural network-based sequence-to-sequence (seq2seq) models strongly suffer from the low-diversity problem when it comes to open-domain dialogue generation. As bland and generic utt…
Extremely Small BERT Models from Mixed-Vocabulary Training
Sanqiang Zhao, Raghav Gupta, Yang Song +1
Pretrained language models like BERT have achieved good results on NLP tasks, but are impractical on resource-limited devices due to memory footprint. A large fraction of this foot…
Informative Image Captioning with External Sources of Information
Sanqiang Zhao, Piyush Sharma, Tomer Levinboim +1
An image caption should fluently present the essential information in a given image, including informative, fine-grained entity mentions and the manner in which these entities inte…
Integrating Transformer and Paraphrase Rules for Sentence Simplification
Sanqiang Zhao, Rui Meng, Daqing He +2
Sentence simplification aims to reduce the complexity of a sentence while retaining its original meaning. Current models for sentence simplification adopted ideas from ma- chine tr…
Deep Keyphrase Generation
Rui Meng, Sanqiang Zhao, Shuguang Han +3
Keyphrase provides highly-condensed information that can be effectively used for understanding, organizing and retrieving text content. Though previous studies have provided many w…