activity
20182021
most citedPAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval

38 citations · 80 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2021★ 38 cited

PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval

Ruiyang Ren, Shangwen Lv, Yingqi Qu +6

Recently, dense passage retrieval has become a mainstream approach to finding relevant information in various natural language processing tasks. A number of studies have been devot…

cs.CL2020★ 7 cited

Pre-training Text Representations as Meta Learning

Shangwen Lv, Yuechen Wang, Daya Guo +10

Pre-training text representations has recently been shown to significantly improve the state-of-the-art in many natural language processing tasks. The central goal of pre-training…

cs.CL2019★ 1 cited

Learning review representations from user and product level information for spam detection

Chunyuan Yuan, Wei Zhou, Qianwen Ma +3

Opinion spam has become a widespread problem in social media, where hired spammers write deceptive reviews to promote or demote products to mislead the consumers for profit or fame…

cs.CL2019★ 21 cited

Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering

Shangwen Lv, Daya Guo, Jingjing Xu +7

Commonsense question answering aims to answer questions which require background knowledge that is not explicitly expressed in the question. The key challenge is how to obtain evid…

cs.CL2018★ 13 cited

Conditional BERT Contextual Augmentation

Xing Wu, Shangwen Lv, Liangjun Zang +2

We propose a novel data augmentation method for labeled sentences called conditional BERT contextual augmentation. Data augmentation methods are often applied to prevent overfittin…