Similar to the "previously-on" scenes in TV shows, recaps can help book reading by recalling the readers' memory about the important elements in previous texts to better understand the ongoing plot. Despite its usefulness, this application has not been well studied in the NLP community. We propose the first benchmark on this useful task called Recap Snippet Identification with a hand-crafted evaluation dataset. Our experiments show that the proposed task is challenging to PLMs, LLMs, and proposed methods as the task requires a deep understanding of the plot correlation between snippets.

翻译：类似于电视剧中的“前情提要”场景，摘要片段能够通过唤起读者对前文中重要元素的记忆，帮助其更好地理解当前情节。尽管该应用极具实用性，但在自然语言处理领域尚未得到充分研究。我们首次提出了名为“摘要片段识别”的实用性任务基准，并构建了人工标注的评估数据集。实验表明，该任务对预训练语言模型、大语言模型及所提方法均构成挑战，因其要求对片段间情节关联性进行深层理解。