activity
20192022
most citedJAKET: Joint Pre-training of Knowledge Graph and Language Understanding

22 citations · 25 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG20223 cited

Long-tailed Extreme Multi-label Text Classification with Generated Pseudo Label Descriptions

Ruohong Zhang, Yau-Shian Wang, Yiming Yang +3

Extreme Multi-label Text Classification (XMTC) has been a tough challenge in machine learning research and applications due to the sheer sizes of the label spaces and the severe da…

cs.CL202022 cited

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,…

cs.LG2020

Knowledge Embedding Based Graph Convolutional Network

Donghan Yu, Yiming Yang, Ruohong Zhang +1

Recently, a considerable literature has grown up around the theme of Graph Convolutional Network (GCN). How to effectively leverage the rich structural information in complex graph…

cs.LG2020

Correlation-aware Unsupervised Change-point Detection via Graph Neural Networks

Ruohong Zhang, Yu Hao, Donghan Yu +3

Change-point detection (CPD) aims to detect abrupt changes over time series data. Intuitively, effective CPD over multivariate time series should require explicit modeling of the d…

cs.LG2019

Graph-Revised Convolutional Network

Donghan Yu, Ruohong Zhang, Zhengbao Jiang +2

Graph Convolutional Networks (GCNs) have received increasing attention in the machine learning community for effectively leveraging both the content features of nodes and the linka…