GPT Models Fail to Find Language Structure in the Voynich Manuscript
#12
magnesium 
This could be interesting to test systematically with different kinds of ciphertexts. Are there classes of substitution ciphers, for instance, that produce readily decipherable ciphertexts that exhibit anomalously low, VMS-like GPT predictability? If a given type of cipher, encrypting a wide range of plaintexts, consistently appears to be more GPT-predictable than the VMS, than that kind of cipher probably isn't consistent with the VMS. But this method probably would be overkill: Monoalphabetic substitution ciphers would probably show up as much more predictable in this analysis than the VMS, but we can rule out monoalphabetic substitution ciphers using much less computationally expensive techniques.
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I will work with the ciphers and the GPT

(02-07-2025, 08:26 PM)Koen G wrote: You are not allowed to view links. Register or Login to view.[quote="quimqu" pid='68392' dateline='1751479547']This also makes me wonder: are you suggesting that Voynichese might behave similarly because it encodes something like a “morphologically rich” or non-repetitive learned language — perhaps even analogous to medieval Latin?

I don't think so. If you remove all potential suffixes from Voynichese, there's not enough left in terms of roots. At least that's my intuitive feeling about it. Maybe it's worth an experiment.

Interesting!
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RE: GPT Models Fail to Find Language Structure in the Voynich Manuscript - by quimqu - 02-07-2025, 08:46 PM

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