this post was submitted on 09 Jul 2026
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Abstract page for arXiv paper 2604.03136: StoryScope: Investigating idiosyncrasies in AI fiction

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[–] AnAmericanPotato@programming.dev 76 points 1 day ago (2 children)

93.2% macro-F1 for human vs. AI detection and 68.4% macro-F1 for six-way authorship attribution

This isn't what I'd call "reliable".

I'm also not impressed with their methodology, which is heavily based on Gemini.

To generate mirrored AI stories, we reverse-engineer writing prompts from each human story by prompting Gemini 2.5 Flash (Gemini Team, 2025a) to infer the underlying premise

That's too many steps removed from anything you'd encounter in the wild. They're not even testing against human-prompted output.

And then they use Gemini again to analyze all the stories. Relying on proprietary cloud models for the core of your analysis is like building on sand.

[–] MangoCats@feddit.it 11 points 1 day ago

Next up: AI adapts to evade detection by last week's researchers' detectors.