"The researchers hypothesize that GPT-style generative models, and similar types of language generation frameworks, have been used to produce much of the text i

"The researchers hypothesize that GPT-style generative models, and similar types of language generation frameworks, have been used to produce much of the text in the flagged papers; however, the way that a generative model abstracts its sources makes this difficult to prove, and the chief evidence lies in a common-sense evaluation of poor and unnecessary synonyms, and a meticulous examination of the submission’s logical coherence." This sounds extremely unlikely. First, scientific fraudsters are typically extremely lazy; they do not use fancy methods like writing generative models of fake data to ensure the numbers, say, add up to 100%, much less neural nets. (Do we believe that someone would go to the effort of setting up GPT to generate fake papers and then be satisfied with results like 'profound neural organization'? Easier to write such garbage by hand!) Second, the given examples are so bad I'm insulted on behalf of GPT: 'profound neural organization' looks like a word-by-word calque using a thesaurus or particularly antiquated machine translation (in a "the vodka is good, but the meat is rotten" way), no contemporary AI involved; GPT would not generate such garbage. Third, if GPT was generating these papers, it would be easy to detect by looking for top-k signatures, using GPT-targeted classifiers (they get >90% accuracy), or looking for stylistic tics of GPT; that they don't provide any specific GPT-like aspects of the text suggests there are none.