119 citations · 199 across the 5 of their papers we have counts for
5 papers
JAKET: Joint Pre-training of Knowledge Graph and Language Understanding
Donghan Yu, Chenguang Zhu, Yiming Yang +1
Knowledge graphs (KGs) contain rich information about world knowledge, entities and relations. Thus, they can be great supplements to existing pre-trained language models. However,…
Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization
Beliz Gunel, Chenguang Zhu, Michael Zeng +1
Neural models have become successful at producing abstractive summaries that are human-readable and fluent. However, these models have two critical shortcomings: they often don't r…
Few-shot Natural Language Generation for Task-Oriented Dialog
Baolin Peng, Chenguang Zhu, Chunyuan Li +4
As a crucial component in task-oriented dialog systems, the Natural Language Generation (NLG) module converts a dialog act represented in a semantic form into a response in natural…
SIM: A Slot-Independent Neural Model for Dialogue State Tracking
Chenguang Zhu, Michael Zeng, Xuedong Huang
Dialogue state tracking is an important component in task-oriented dialogue systems to identify users' goals and requests as a dialogue proceeds. However, as most previous models a…
SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering
Chenguang Zhu, Michael Zeng, Xuedong Huang
Conversational question answering (CQA) is a novel QA task that requires understanding of dialogue context. Different from traditional single-turn machine reading comprehension (MR…