Multimodal Abstractive Text Summarization

Multimodal Abstractive Text Summarization is a subtask in the field of natural language processing that aims to generate richer and more accurate summary content by integrating information from multiple modalities (such as text, images, audio, etc.). This task not only focuses on the extraction and reorganization of textual information but also emphasizes the fusion and understanding of cross-modal information to enhance the comprehensiveness and expressiveness of the summary. Its application value lies in providing users with a more intuitive and diversified overview of information, suitable for various scenarios including news reporting, academic research, social media, and more.