Computer-aided process planning is the bridge between computer-aided design and
computer-aided manufacturing. With the advent of the intelligent manufacturing era, process …

Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training
paradigm, successfully introduces text supervision to vision models. It has shown promising …

Graph neural networks (GNN) have emerged as a new state-of-the-art for learning
knowledge graph representations. Although they have shown impressive performance in …

A vast amount of textual and structural information is required for knowledge graph
construction and its downstream tasks. However, most of the current knowledge graphs are …

Abstract Knowledge graphs, modeling multi-relational data, improve numerous applications
such as question answering or graph logical reasoning. Many graph neural networks for …

Knowledge graph completion (KGC) aims to study the embedding representation to solve
the incompleteness of knowledge graphs (KGs). Recently, graph convolutional networks …

Transformers have achieved remarkable performance in widespread fields, including
natural language processing, computer vision and graph mining. However, vanilla …

Graph Neural Networks (GNNs) have demonstrated great success in Knowledge Graph
Completion (KGC) by modeling how entities and relations interact in recent years. However …

Recently decades have witnessed the empirical success of framing Knowledge Graph (KG)
embeddings via language models. However, language model-based KG embeddings are …

Graph neural networks (GNNs), which effectively use topological structures in the
knowledge graphs (KG) to embed entities and relations in low-dimensional spaces, have …