Earlier quoted context omitted.
> which inherently compromises quality. I don’t see how this follows? Tokens are chosen randomly. If you choose tokens with a different RNG in the same distribution, you’re still getting equally good or bad tokens.
Not all values of "equally good" are equally good. Writing has rhythm, or at least it's supposed to, and synonym swapping compromises it. Never mind metaphors and similes, which are even more tightly constrained. LLM writing is still a long way from good. Sometimes you get lucky with the odd line, but there's a difference in quality between influencer slop, genre fiction, and literary fiction and/or best-in-class jou…
We already know that a non-zero temperature improves quality though with current models (particularly with creative writing). The assumption that always picking the 'best' token results in the 'best' output is not the current reality.
And if you are already intentionally putting in randomness, I can imagine that it would be possible to seed the randomness in a way that is detectable but results in the same quality.
This is obviously not true for queries where temp = 0, but at temp = 0 then it becomes easier to identify anyway. I assume this technique implies some level of temperature.