Advances and Challenges in Multimodal Entity Linking: A Comprehensive Survey

This study offers a comprehensive examination of the recent advances and challenges in multimodal entity linking (MEL). The paper begins by outlining the background of the growth of multimodal data and the significance of knowledge bases. It provides a detailed description of the definition and architecture of the MEL task. Through an extensive analysis of existing methods, datasets, and evaluation metrics, this paper highlights the potential of MEL to enhance information retrieval accuracy and facilitate knowledge graph construction. The study indicates that, despite significant progress in the MEL field, challenges remain, including issues related to data quality, model generalization, model interpretability and multimodal fusion technologies. Finally, the paper proposes future research directions, such as the application of large language model and the development of scientific theories related to multimodal information fusion and disambiguation, thereby offering clear guidance for subsequent research.