Abstract Knowledge graphs are large-scale semantic networks that considerably impact
knowledge representation. Mining hidden knowledge from existing data, including triplet …

Commonsense reasoning based on knowledge graphs (KGs) is a challenging task that
requires predicting complex questions over the described textual contexts and relevant …

Narratives is an account of the unfolding of events, along with explanations of how and why
these processes and events came to be. To understand narratives, causality has been …

Intuitively, humans can consciously and subjectively attend to the interactions between
objects, and thus infer reasonable visual relations. However, mainstream approaches of …

Most methods cannot segment the semantic regions accurately due to the lack of global-
level supervision or guidance of external knowledge. To overcome this limitation, we …

Abstract Machine reading comprehension (MRC) is a fundamental task of evaluating the
natural language understanding ability of model, which requires complicated reasoning …

Deep learning significantly impacts neural network controller synthesis. Despite the higher
efficiency of deep learning algorithms compared to traditional model-based controller design …

As an important and challenging problem in computer vision, scene graph generation (SGG)
aims to find out the underlying semantic relationships among objects from a given image for …

In order to solve outdoor mobile robots' dependence on geographic information systems,
and to realize automatic navigation in the face of complex and changeable scenes, we …

Visual relationship detection is crucial for understanding visual scenes and is widely used in
many areas, including visual navigation, visual question answering, and machine trouble …