  Narrative visualization effectively transforms data into engaging stories,
making complex information accessible to a broad audience. Large models,
essential for narrative visualization, inherently facilitate this process
through their superior ability to handle natural language queries and answers,
generate cohesive narratives, and enhance visual communication. Inspired by
previous work in narrative visualization and recent advances in large models,
we synthesized potential tasks and opportunities for large models at various
stages of narrative visualization. In our study, we surveyed 79 papers to
explore the role of large models in automating narrative visualization
creation. We propose a comprehensive pipeline that leverages large models for
crafting narrative visualization, categorizing the reviewed literature into
four essential phases: Data, Narration, Visualization, and Presentation.
Additionally, we identify nine specific tasks where large models are applied
across these stages. This study maps out the landscape of challenges and
opportunities in the LM4NV process, providing insightful directions for future
research and valuable guidance for scholars in the field.
