3 accepted papers
Dense passage retrieval has become the mainstream method in the first stage of open-domain question answering, which usually adopts a bi-encoder structure to learn the dense representation of questions and passages for semantic matching. One of the main challenges currently is to effectively utilize…
Relation prediction on knowledge graphs (KGs) attempts to infer the missing links between entities. Most previous studies are limited to the transductive setting where all entities must be seen during the training, making them unable to perform reasoning on emerging entities. Recently, the inductive…
Cross-lingual entity alignment, which aims to match equivalent entities in KGs with different languages, has attracted considerable focus in recent years. Recently, many graph neural network (GNN) based methods are proposed for entity alignment and obtain promising results. However, existing GNN-bas…