20 citations · 32 across the 4 of their papers we have counts for
4 papers
Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization
Hai Ye, Wenjie Li, Lu Wang
Semantic parsing aims to transform natural language (NL) utterances into formal meaning representations (MRs), whereas an NL generator achieves the reverse: producing a NL descript…
BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization
Eva Sharma, Chen Li, Lu Wang
Most existing text summarization datasets are compiled from the news domain, where summaries have a flattened discourse structure. In such datasets, summary-worthy content often ap…
A Pilot Study of Domain Adaptation Effect for Neural Abstractive Summarization
Xinyu Hua, Lu Wang
We study the problem of domain adaptation for neural abstractive summarization. We make initial efforts in investigating what information can be transferred to a new domain. Experi…
Joint Modeling of Content and Discourse Relations in Dialogues
Kechen Qin, Lu Wang, Joseph Kim
We present a joint modeling approach to identify salient discussion points in spoken meetings as well as to label the discourse relations between speaker turns. A variation of our…