Narrative Alignment

Narrative alignment focuses on computationally identifying and measuring correspondences between narrative structures across different media and versions, aiming to understand how stories are transformed and interpreted. Current research employs techniques like the Smith-Waterman algorithm, coupled with embeddings from large language models, to align texts, videos, and even comic sequences, analyzing aspects such as causal-temporal relationships and character consistency. This work has implications for fields ranging from literary analysis and film studies to the development of more sophisticated AI systems for content generation and understanding, particularly in video captioning and story visualization.