mlsanityData to 7 Oct 2026

Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books

arXiv 2601.18353 ↗First posted 26 Jan 2026cs.AI cs.CL cs.HCcited by 9

Not on the map. Why?

Abstract (arXiv)

Creative writing has long been considered a uniquely human endeavor, requiring voice and style that machines could not replicate. This assumption is challenged by Generative AI that can emulate thousands of author styles in seconds with negligible marginal labor. To understand this better, we conducted a behavioral experiment where 28 MFA writers (experts) competed against three LLMs in emulating 50 critically acclaimed authors. Based on blind pairwise comparisons by 28 expert judges and 131 lay judges, we find that experts preferred human writing in 82.7% of cases under the in-context prompting condition but this reversed to 62% preference for AI after fine-tuning on authors' complete works. Lay judges, however, consistently preferred AI writing. Debrief interviews with expert writers revealed that their preference for AI writing triggered an identity crisis, eroding aesthetic confidence and questioning what constitutes "good writing." These findings challenge discourse about AI's creative limitations and raise fundamental questions about the future of creative labor.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 30 of its 74 references that are in the map. First posted on arXiv 26 Jan 2026.

Builds on

30 of 74 references.

References · 30

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
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18 more
  1. 2025The Widespread Adoption of Large Language Model-Assisted Writing Across Societycited by 50
  2. 2024Can AI writing be salvaged? Mitigating Idiosyncrasies and Improving Human-AI Alignment in the Writing Process through Editscited by 49
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  12. 2024Copying style, Extracting value: Illustrators' Perception of AI Style Transfer and its Impact on Creative Laborcited by 8
  13. 2025Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writerscited by 8
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  15. 2024Creative Writers' Attitudes on Writing as Training Data for Large Language Modelscited by 4
  16. 2025Phraselette: A Poet's Procedural Palettecited by 4
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 9.

9 papers.

  1. 2026Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Modelscited by 6
  2. 2026AI Fiction in the Wildcited by 2
  3. 2026Generative AI floods and dilutes the market for bookscited by 2
  4. 2026The Ultimate Tutorial for AI-driven Scale Development in Generative Psychometrics: Releasing AIGENIE from its Bottlecited by 1
  5. 2026Ex Ante Evaluation of AI-Induced Idea Diversity Collapsecited by 1
  6. 2026Narrative Flattening: How Post-Training Compresses Thematic, Affective, and Stylistic Variation in LLM Fictioncited by 1
  7. 2026Do Large Language Models Always Tell The Same Stories?cited by 1
  8. 2026Characterizing Cultural Localization in AI-Generated Storiescited by 0
  9. 2026Weightless Fine-Tuning: Personalizing LLMs via Logit-Space Transportcited by 0