most citedEnd-to-End Answer Chunk Extraction and Ranking for Reading Comprehension

42 citations · 46 across the 3 of their papers we have counts for

collaborators

12 papers

cs.CL20191 cited

Multi-Granular Text Encoding for Self-Explaining Categorization

Zhiguo Wang, Yue Zhang, Mo Yu +5

Self-explaining text categorization requires a classifier to make a prediction along with supporting evidence. A popular type of evidence is sub-sequences extracted from the input…

cs.CL20193 cited

TWEETQA: A Social Media Focused Question Answering Dataset

Wenhan Xiong, Jiawei Wu, Hong Wang +5

With social media becoming increasingly pop-ular on which lots of news and real-time eventsare reported, developing automated questionanswering systems is critical to the effective…

cs.CL20196 cited

Self-Supervised Learning for Contextualized Extractive Summarization

Hong Wang, Xin Wang, Wenhan Xiong +4

Existing models for extractive summarization are usually trained from scratch with a cross-entropy loss, which does not explicitly capture the global context at the document level.…

cs.CL20193 cited

Selection Bias Explorations and Debias Methods for Natural Language Sentence Matching Datasets

Guanhua Zhang, Bing Bai, Jian Liang +5

Natural Language Sentence Matching (NLSM) has gained substantial attention from both academics and the industry, and rich public datasets contribute a lot to this process. However,…

cs.CL201917 cited

Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

Wenhan Xiong, Mo Yu, Shiyu Chang +2

We propose a new end-to-end question answering model, which learns to aggregate answer evidence from an incomplete knowledge base (KB) and a set of retrieved text snippets. Under t…

cs.LG2019129 cited

DAG-GNN: DAG Structure Learning with Graph Neural Networks

Yue Yu, Jie Chen, Tian Gao +1

Learning a faithful directed acyclic graph (DAG) from samples of a joint distribution is a challenging combinatorial problem, owing to the intractable search space superexponential…