Attention Flows: Tracing LLM Conceptual Engagement via Story Summaries

Researchers evaluated whether large language models understand long-form narratives similarly to humans by comparing summaries of 150 novels written by humans and nine state-of-the-art LLMs. The study found that LLMs focus disproportionately on story endings rather than distributing attention like human readers, revealing gaps in narrative comprehension despite expanded context windows.