98 citations · 209 across the 9 of their papers we have counts for
9 papers
Open-Domain Event Graph Induction for Mitigating Framing Bias
Siyi Liu, Hongming Zhang, Hongwei Wang +3
Researchers have proposed various information extraction (IE) techniques to convert news articles into structured knowledge for news understanding. However, none of the existing me…
Schema-Guided Event Graph Completion
Hongwei Wang, Zixuan Zhang, Sha Li +5
We tackle a new task, event graph completion, which aims to predict missing event nodes for event graphs. Existing link prediction or graph completion methods have difficulty deali…
Chemical-Reaction-Aware Molecule Representation Learning
Hongwei Wang, Weijiang Li, Xiaomeng Jin +4
Molecule representation learning (MRL) methods aim to embed molecules into a real vector space. However, existing SMILES-based (Simplified Molecular-Input Line-Entry System) or GNN…
RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representation
En Yu, Zhuoling Li, Shoudong Han +1
Existing online multiple object tracking (MOT) algorithms often consist of two subtasks, detection and re-identification (ReID). In order to enhance the inference speed and reduce…
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning
Pan Li, Yanbang Wang, Hongwei Wang +1
Learning representations of sets of nodes in a graph is crucial for applications ranging from node-role discovery to link prediction and molecule classification. Graph Neural Netwo…
MAT: Motion-Aware Multi-Object Tracking
Shoudong Han, Piao Huang, Hongwei Wang +4
Modern multi-object tracking (MOT) systems usually model the trajectories by associating per-frame detections. However, when camera motion, fast motion, and occlusion challenges oc…
Refinements in Motion and Appearance for Online Multi-Object Tracking
Piao Huang, Shoudong Han, Jun Zhao +4
Modern multi-object tracking (MOT) system usually involves separated modules, such as motion model for location and appearance model for data association. However, the compatible p…
Relational Message Passing for Knowledge Graph Completion
Hongwei Wang, Hongyu Ren, Jure Leskovec
Knowledge graph completion aims to predict missing relations between entities in a knowledge graph. In this work, we propose a relational message passing method for knowledge graph…
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
Hongwei Wang, Fuzheng Zhang, Mengdi Zhang +4
Knowledge graphs capture structured information and relations between a set of entities or items. As such knowledge graphs represent an attractive source of information that could…