Imbalanced node classification widely exists in real-world networks wher...
In recent years, deep convolutional neural networks (CNN) have significa...
Distilling supervision signal from a long sequence to make predictions i...
Question answering over temporal knowledge graphs (KGs) efficiently uses...
Recent work on aspect-level sentiment classification has demonstrated th...
Recommending appropriate algorithms to a classification problem is one o...
Introducing self-attention mechanism in graph neural networks (GNNs) ach...
Commonsense knowledge graph (CKG) is a special type of knowledge graph (...
Document-level relation extraction is a challenging task which requires
...
Translational distance-based knowledge graph embedding has shown progres...
Interpretable multi-hop reading comprehension (RC) over multiple documen...
Graph Attention Networks (GATs) are the state-of-the-art neural architec...
Aspect-level sentiment classification aims to identify the sentiment pol...
Multi-hop reading comprehension (RC) across documents poses new challeng...