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20172022
most citedTaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network

56 citations · 203 across the 18 of their papers we have counts for

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17 papers · 1 filter

cs.CL2022

Topic Taxonomy Expansion via Hierarchy-Aware Topic Phrase Generation

Dongha Lee, Jiaming Shen, Seonghyeon Lee +3

Topic taxonomies display hierarchical topic structures of a text corpus and provide topical knowledge to enhance various NLP applications. To dynamically incorporate new topic info…

cs.CL20215 cited

Who Should Go First? A Self-Supervised Concept Sorting Model for Improving Taxonomy Expansion

Xiangchen Song, Jiaming Shen, Jieyu Zhang +1

Taxonomies have been widely used in various machine learning and text mining systems to organize knowledge and facilitate downstream tasks. One critical challenge is that, as data…

cs.CL20212 cited

Taxonomy Completion via Triplet Matching Network

Jieyu Zhang, Xiangchen Song, Ying Zeng +4

Automatically constructing taxonomy finds many applications in e-commerce and web search. One critical challenge is as data and business scope grow in real applications, new concep…

cs.CL2020

Near-imperceptible Neural Linguistic Steganography via Self-Adjusting Arithmetic Coding

Jiaming Shen, Heng Ji, Jiawei Han

Linguistic steganography studies how to hide secret messages in natural language cover texts. Traditional methods aim to transform a secret message into an innocent text via lexica…

cs.CL2020

SynSetExpan: An Iterative Framework for Joint Entity Set Expansion and Synonym Discovery

Jiaming Shen, Wenda Qiu, Jingbo Shang +3

Entity set expansion and synonym discovery are two critical NLP tasks. Previous studies accomplish them separately, without exploring their interdependencies. In this work, we hypo…

cs.CL202047 cited

STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths

Yue Yu, Yinghao Li, Jiaming Shen +3

Taxonomies are important knowledge ontologies that underpin numerous applications on a daily basis, but many taxonomies used in practice suffer from the low coverage issue. We stud…