6 citations · 20 across the 6 of their papers we have counts for
6 papers
Unsupervised Dialogue Topic Segmentation with Topic-aware Utterance Representation
Haoyu Gao, Rui Wang, Ting-En Lin +4
Dialogue Topic Segmentation (DTS) plays an essential role in a variety of dialogue modeling tasks. Previous DTS methods either focus on semantic similarity or dialogue coherence to…
Neural Topic Modeling by Incorporating Document Relationship Graph
Deyu Zhou, Xuemeng Hu, Rui Wang
Graph Neural Networks (GNNs) that capture the relationships between graph nodes via message passing have been a hot research direction in the natural language processing community.…
Neural Topic Modeling with Cycle-Consistent Adversarial Training
Xuemeng Hu, Rui Wang, Deyu Zhou +1
Advances on deep generative models have attracted significant research interest in neural topic modeling. The recently proposed Adversarial-neural Topic Model models topics with an…
Neural Topic Modeling with Bidirectional Adversarial Training
Rui Wang, Xuemeng Hu, Deyu Zhou +4
Recent years have witnessed a surge of interests of using neural topic models for automatic topic extraction from text, since they avoid the complicated mathematical derivations fo…
Open Event Extraction from Online Text using a Generative Adversarial Network
Rui Wang, Deyu Zhou, Yulan He
To extract the structured representations of open-domain events, Bayesian graphical models have made some progress. However, these approaches typically assume that all words in a d…
ATM:Adversarial-neural Topic Model
Rui Wang, Deyu Zhou, Yulan He
Topic models are widely used for thematic structure discovery in text. But traditional topic models often require dedicated inference procedures for specific tasks at hand. Also, t…