16 citations · 42 across the 4 of their papers we have counts for
4 papers
NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
Mikhail Galkin, Etienne Denis, Jiapeng Wu +1
Conventional representation learning algorithms for knowledge graphs (KG) map each entity to a unique embedding vector. Such a shallow lookup results in a linear growth of memory c…
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion
Jiapeng Wu, Yishi Xu, Yingxue Zhang +3
Reasoning in a temporal knowledge graph (TKG) is a critical task for information retrieval and semantic search. It is particularly challenging when the TKG is updated frequently. T…
TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
Jiapeng Wu, Meng Cao, Jackie Chi Kit Cheung +1
Inferring missing facts in temporal knowledge graphs (TKGs) is a fundamental and challenging task. Previous works have approached this problem by augmenting methods for static know…
Factual Error Correction for Abstractive Summarization Models
Meng Cao, Yue Dong, Jiapeng Wu +1
Neural abstractive summarization systems have achieved promising progress, thanks to the availability of large-scale datasets and models pre-trained with self-supervised methods. H…