activity
20172023
most citedSDNet: Contextualized Attention-based Deep Network for Conversational Question Answering

119 citations · 587 across the 48 of their papers we have counts for

collaborators
Showing 2020Show all

9 papers · 1 filter

cs.CL2020★ 7 cited

RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems

Baolin Peng, Chunyuan Li, Zhu Zhang +3

For task-oriented dialog systems to be maximally useful, it must be able to process conversations in a way that is (1) generalizable with a small number of training examples for ne…

cs.CL2020

Mixed-Lingual Pre-training for Cross-lingual Summarization

Ruochen Xu, Chenguang Zhu, Yu Shi +2

Cross-lingual Summarization (CLS) aims at producing a summary in the target language for an article in the source language. Traditional solutions employ a two-step approach, i.e. t…

cs.CL2020

A Survey of Knowledge-Enhanced Text Generation

Wenhao Yu, Chenguang Zhu, Zaitang Li +4

The goal of text generation is to make machines express in human language. It is one of the most important yet challenging tasks in natural language processing (NLP). Since 2014, v…

cs.CL2020

Injecting Entity Types into Entity-Guided Text Generation

Xiangyu Dong, Wenhao Yu, Chenguang Zhu +1

Recent successes in deep generative modeling have led to significant advances in natural language generation (NLG). Incorporating entities into neural generation models has demonst…

cs.CL2020★ 27 cited

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…

cs.CL2020

Data Augmentation for Spoken Language Understanding via Pretrained Language Models

Baolin Peng, Chenguang Zhu, Michael Zeng +1

The training of spoken language understanding (SLU) models often faces the problem of data scarcity. In this paper, we put forward a data augmentation method using pretrained langu…