This doesn‘t sound like AI. LLMs do not use dictionary definitions for translating a paper this way. It does look like some translation engine like Google Translate or worse, maybe with some text obfuscator trying to avoid plagiarism detection.
The simplest way to build autocorrect is to have a dictionary, look it up for each word, and suggest the "closest" dictionary word if a typed word is absent from the dictionary.
It has existed way before transformers and on platforms that couldn't dream of running even the smallest transformer.
I think you'll find the broader idea of word vectorization to be remarkably similar to what text transformers do.
We're just talking past each other. I agree that a tree is the historical solution. I didn't catch that part.
Most people seem to believe LLM only describe these decoder-only architectures, but the term predate them by a big margin. BERT (encoder-only) was a large language model, and there were even language models before transformers were even a thing.
Wouldn't that mean that checking the watermark...
(1) Required knowing the prompt used to generate the text; and
(2) was just as expensive as generating the text?
(One approach that's been described is creating a bias in certain token pairs or short sequences: by hashing the previous n tokens, potentially with a secret seed, you create a list of essentially random allowed and disallowed next tokens, then bias the token selection to prefer allowed tokens, so long as they are plausible enough. Then you can check any long-enough subset of the output, if it deviates significantly enough from random chance on following this rule, it was almost certainly generated from a system following these rules.)
The changes they made often resulted in this kind of weird nonsense: Swapping the word "Failure" for "Disappointment" in a vain attempt to keep it from saying "you're a failure", but also just stripping out words such as slurs and insults, resulting in at one point the hilarious situation in which Gemini for quite a while would INSIST that the lyrics for the Dire Straits song "Money for Nothing" contained "That little has his own jet airplane/that little is a millionaire" -- which in certain contexts changes the meaning of the song incredibly.
These hack-and-slash text manglings have resulted in some of these clbuttic sort of writing styles being used during LLM-assisted writing. A more famous version of this was caused by one paper: https://world.edu/a-weird-phrase-is-plaguing-scientific-pape...