206 citations · 624 across the 70 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.LG2019★ 1 cited
Neural Subgraph Isomorphism Counting
Xin Liu, Haojie Pan, Mutian He +3
In this paper, we study a new graph learning problem: learning to count subgraph isomorphisms. Different from other traditional graph learning problems such as node classification…
cs.CL2019★ 41 cited
Integrating Graph Contextualized Knowledge into Pre-trained Language Models
Bin He, Di Zhou, Jinghui Xiao +4
Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information. However, traditional methods usually treat a triple as a t…
cs.CL2019★ 16 cited
Pretrained Language Models for Document-Level Neural Machine Translation
Liangyou Li, Xin Jiang, Qun Liu
Previous work on document-level NMT usually focuses on limited contexts because of degraded performance on larger contexts. In this paper, we investigate on using large contexts wi…