mlsanityData to 7 Oct 2026

Previously on the Stories: Recap Snippet Identification for Story Reading

arXiv 2402.07271 ↗First posted 11 Feb 2024cs.CLcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 32 references that are in the map. First posted on arXiv 11 Feb 2024.

Builds on

24 of 32 references.

References · 24

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12 more
  1. 2021"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understandingcited by 48
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Cited by year

Citing papers per year: 2024: 1; 2025: 2.

3 papers.

  1. 2024Fine-Grained Modeling of Narrative Context: A Coherence Perspective via Retrospective Questionscited by 11
  2. 2025The Stochastic Parrot on LLM's Shoulder: A Summative Assessment of Physical Concept Understandingcited by 11
  3. 2025SitEmb-v1.5: Improved Context-Aware Dense Retrieval for Semantic Association and Long Story Comprehensioncited by 8