activity
20142021
most citedA Survey on Text Classification: From Shallow to Deep Learning

101 citations · 423 across the 19 of their papers we have counts for

collaborators

19 papers

cs.LG2021★ 38 cited

ACE-HGNN: Adaptive Curvature Exploration Hyperbolic Graph Neural Network

Xingcheng Fu, Jianxin Li, Jia Wu +6

Graph Neural Networks (GNNs) have been widely studied in various graph data mining tasks. Most existingGNNs embed graph data into Euclidean space and thus are less effective to cap…

cs.CR2021★ 8 cited

HAWK: Rapid Android Malware Detection through Heterogeneous Graph Attention Networks

Yiming Hei, Renyu Yang, Hao Peng +6

Android is undergoing unprecedented malicious threats daily, but the existing methods for malware detection often fail to cope with evolving camouflage in malware. To address this…

cs.CL2021★ 1 cited

Event Extraction by Associating Event Types and Argument Roles

Qian Li, Shu Guo, Jia Wu +5

Event extraction (EE), which acquires structural event knowledge from texts, can be divided into two sub-tasks: event type classification and element extraction (namely identifying…

cs.LG2021★ 8 cited

Transferring Knowledge Distillation for Multilingual Social Event Detection

Jiaqian Ren, Hao Peng, Lei Jiang +6

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages…

cs.CL2021

Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations

Qian Li, Hao Peng, Jianxin Li +5

Event extraction is a fundamental task for natural language processing. Finding the roles of event arguments like event participants is essential for event extraction. However, doi…

cs.AI2021★ 3 cited

Federated Multi-View Learning for Private Medical Data Integration and Analysis

Sicong Che, Hao Peng, Lichao Sun +2

Along with the rapid expansion of information technology and digitalization of health data, there is an increasing concern on maintaining data privacy while garnering the benefits…