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submitted 21 hours ago by Allah@piefed.world to c/technology@lemmy.world

Abstract page for arXiv paper 2604.03136: StoryScope: Investigating idiosyncrasies in AI fiction

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[-] AnAmericanPotato@programming.dev 56 points 19 hours ago

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 5 points 13 hours ago

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

this post was submitted on 09 Jul 2026
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