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 ten 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.

翻译：叙事可视化有效地将数据转化为引人入胜的故事，使复杂信息能被广大受众所理解。大型模型作为叙事可视化的核心要素，通过其处理自然语言问答、生成连贯叙事以及增强视觉沟通的卓越能力，天然地促进了这一过程。受前人关于叙事可视化研究以及大型模型最新进展的启发，我们综合归纳了大型模型在叙事可视化各阶段中的潜在任务与机遇。本研究调研了79篇论文，以探讨大型模型在自动化叙事可视化创作中的作用。我们提出了一套利用大型模型构建叙事可视化的完整流程，将所综述文献归纳为四大关键阶段：数据、叙事、可视化与呈现。此外，我们识别出大型模型在这些阶段中应用的十项具体任务。本研究勾勒出LM4NV流程中的挑战与机遇图景，为未来研究提供了具有洞察力的方向，并为该领域学者提供了有价值的指导。