39 citations · 63 across the 24 of their papers we have counts for
3 papers · 1 filter
Relation-Aware Language-Graph Transformer for Question Answering
Jinyoung Park, Hyeong Kyu Choi, Juyeon Ko +5
Question Answering (QA) is a task that entails reasoning over natural language contexts, and many relevant works augment language models (LMs) with graph neural networks (GNNs) to…
Deformable Graph Transformer
Jinyoung Park, Seongjun Yun, Hyeonjin Park +5
Transformer-based models have recently shown success in representation learning on graph-structured data beyond natural language processing and computer vision. However, the succes…
Metropolis-Hastings Data Augmentation for Graph Neural Networks
Hyeonjin Park, Seunghun Lee, Sihyeon Kim +5
Graph Neural Networks (GNNs) often suffer from weak-generalization due to sparsely labeled data despite their promising results on various graph-based tasks. Data augmentation is a…