Neural Authorship Attribution: Stylometric Analysis on Large Language Models — mentioned by solardev

Wed, 21 Feb 2024 16:17:29 GMT

Maybe you can't determine that with certainty, but there may be statistical tools you can use to estimate the probably that some content came from one of the LLMs we know about based on their known writing styles? Someone did something like that to identify HN authors (as in correlating similar writing styles between pseudonyms) a few years back, for example: https://news.ycombinator.com/item?id=33755016 Or a study applying similar analysis to LLMs: https://arxiv.org/pdf/2308.07305 Of course, LLM output can be tweaked to evade these, just like humans can alter their writing style or…

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Neural Authorship Attribution: Stylometric Analysis on Large Language Models · HackerPapers discussions

Neural Authorship Attribution: Stylometric Analysis on Large Language Models — mentioned by solardev