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Research paper models novel sequels as geometric transformations in embedding space

By PulseAugur Editorial · [1 sources] ·

A new research paper explores the transformation from an original novel to its sequel by treating books as points in an embedding space. The study decomposes the "displacement" between a novel and its sequel into interpretable geometric components using PCA on paragraph embeddings from the PG19 corpus. This analysis reveals a taxonomy of sequels, categorizing them as formulaic, concentrated, or compositional, and offers insights into the specific geometric changes that define these literary transformations. AI

IMPACT Provides a novel method for analyzing literary structure and authorial intent using NLP techniques.

RANK_REASON The cluster contains a single research paper detailing a novel methodology for analyzing literary transformations using NLP and geometric decomposition. [lever_c_demoted from research: ic=1 ai=0.7]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Research paper models novel sequels as geometric transformations in embedding space

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The cluster contains a single research paper detailing a novel methodology for analyzing literary transformations using NLP and geometric decomposition. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Story Operators: Decomposing the Original $\to$ Sequel Transformation in Embedding Space

    I treat a book as a point in a sentence-embedding space and a literary transformation as an operation on points. Given an original novel and its sequel, I ask what it takes, geometrically, to turn the first into the second. Using all-mpnet-base-v2 paragraph embeddings drawn from …

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