arXiv:2608. 12630v1 Announce Type: cross Abstract: While large language models can generate entire novels, there is little information about the level of formal variation in their output over many generations.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
The study demonstrates that text produced by large language models (LLMs) leaves a distinct stylometric footprint—primarily increased entropy and lexical diversity—across multiple models and domains. In contrast, AI editing of human text does not replicate this footprint; edited texts show only modest lexical diversity gains and reduced entropy, with lexical density emerging as the key distinguishing feature. Consequently, stylometric analysis can differentiate AI-generated from AI-edited content, but is less effective at distinguishing either from purely human writing.
arXiv:2603. 13545v2 Announce Type: replace Abstract: AI development has a fiction dependency problem.
arXiv:2606.26040v2 Announce Type: replace Abstract: AI translation of literary works is increasingly common. While the content may be rendered adequately, we do not know enough about how readers expe...
arXiv:2601. 15828v4 Announce Type: replace-cross Abstract: This study investigates whether professional translators without prior specialized training can reliably identify short stories generated in Italian by artificial intelligence (AI).
arXiv:2601. 17363v3 Announce Type: replace-cross Abstract: This study investigates whether readers prefer AI-generated short stories in Italian over one written by a renowned Italian author.
arXiv:2604. 26269v2 Announce Type: replace-cross Abstract: In the era of large language models, creative writing quality lacks a computable theoretical anchor.