Multi-modal Knowledge Graph Completion: A Survey

In recent years, with the rapid development of artificial intelligence, multi-modal knowledge graph completion (MMKGC) has become increasingly important. Many scholars have conducted in-depth research on multi-modal knowledge graphs (MMKGs), leading to the proposal of numerous MMKGC models. Summarizing the current state of research is crucial for guiding future studies. This survey aims to review the current advanced techniques for MMKGC. By analyzing and elaborating on the value and categories of MMKGs in detail, we summarize the challenges faced by existing MMKGC methods. Our work provides valuable insights and explorations for the research and application of completing MMKGs.