mlsanityData to 14 Oct 2026

Are You There God? Lightweight Narrative Annotation of Christian Fiction with LMs

arXiv 2507.19756 ↗First posted 26 Jul 2025cs.CLcited by 1

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Abstract (arXiv)

In addition to its more widely studied cultural movements, American Evangelicalism has a well-developed but less externally visible literary side. Christian Fiction, however, has been little studied, and what scholarly attention there is has focused on the explosively popular Left Behind series. In this work, we use computational tools to provide both a broad topical overview of Christian Fiction as a genre and a more directed exploration of how its authors depict divine acts. Working with human annotators, we first developed a codebook for identifying "acts of God." We then adapted the codebook for use by a recent, lightweight LM with the assistance of a much larger model. The laptop-scale LM is largely capable of matching human annotations, even when the task is subtle and challenging. Using these annotations, we show that significant and meaningful differences exist between divine acts depicted by the Left Behind books and Christian Fiction more broadly.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 14 of its 56 references that are in the map. First posted on arXiv 26 Jul 2025.

Builds on

14 of 56 references.

References · 14

  1. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  2. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,045
  3. 2023Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolutioncited by 551
  4. 2022Instruction Induction: From Few Examples to Natural Language Task Descriptionscited by 152
  5. 2023Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselvescited by 123
  6. 2023Prompt Engineering a Prompt Engineercited by 53
  7. 2024Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Workscited by 38
  8. 2024Reading Subtext: Evaluating Large Language Models on Short Story Summarization with Writerscited by 19
  9. 2024HEART-felt Narratives: Tracing Empathy and Narrative Style in Personal Stories with LLMscited by 16
  10. 2024Evaluating LLMs for Quotation Attribution in Literary Texts: A Case Study of LLaMa3cited by 8
  11. 2025Classifying Unreliable Narrators with Large Language Modelscited by 4
  12. 2024Show, Don't Tell: Uncovering Implicit Character Portrayal using LLMscited by 3
2 more
  1. 2024Says Who? Effective Zero-Shot Annotation of Focalizationcited by 2
  2. 2025LLM for Comparative Narrative Analysiscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.