mlsanityData to 7 Oct 2026

so much depends / upon / a whitespace: Why Whitespace Matters for Poets and LLMs

arXiv 2510.16713 ↗First posted 19 Oct 2025cs.CLcited by 4

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Abstract (arXiv)

Whitespace is a critical component of poetic form, reflecting both adherence to standardized forms and rebellion against those forms. Each poem's whitespace distribution reflects the artistic choices of the poet and is an integral semantic and spatial feature of the poem. Yet, despite the popularity of poetry as both a long-standing art form and as a generation task for large language models (LLMs), whitespace has not received sufficient attention from the NLP community. Using a corpus of 19k English-language published poems from Poetry Foundation, we investigate how 4k poets have used whitespace in their works. We release a subset of 2.8k public-domain poems with preserved formatting to facilitate further research in this area. We compare whitespace usage in the published poems to (1) 51k LLM-generated poems, and (2) 12k unpublished poems posted in an online community. We also explore whitespace usage across time periods, poetic forms, and data sources. Additionally, we find that different text processing methods can result in significantly different representations of whitespace in poetry data, motivating us to use these poems and whitespace patterns to discuss implications for the processing strategies used to assemble pretraining datasets for LLMs.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 19 of its 84 references that are in the map. First posted on arXiv 19 Oct 2025.

Builds on

19 of 84 references.

References · 19

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  2. 2023The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Onlycited by 755
  3. 2024Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Researchcited by 475
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7 more
  1. 2024Tokenization Matters! Degrading Large Language Models through Challenging Their Tokenizationcited by 32
  2. 2024AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filterscited by 21
  3. 2022ClueWeb22: 10 Billion Web Documents with Visual and Semantic Informationcited by 19
  4. 2024Sonnet or Not, Bot? Poetry Evaluation for Large Models and Datasetscited by 18
  5. 2025Broken Tokens? Your Language Model can Secretly Handle Non-Canonical Tokenizationscited by 16
  6. 2024Vulnerability of LLMs to Vertically Aligned Text Manipulationscited by 6
  7. 2024Locating the Leading Edge of Cultural Changecited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 4.

4 papers.