11–20 of 107 posts
Now that's a challenge.
Also, if you train GPT on the whole corpus of Nature / Science / whatever articles up to, say, 2005, could you feed it leading text about discoveries after 2005 and see if it hypothesizes the justification for those discoveries in the same way that the authors did?
The sad thing is that often there's an equal mental effort to read GPT articles and the real ones. It's as if people are trying to make their papers as incomprehensible as possible.
Quite easy when you know one is fake. Flagging fake articles in a review queue, by abstract only, and when none may exist all the way up to all being fake .... Now that's a challenge. Also, if you train GPT on the whole corpus of Nature / Science / whatever articles up to, say, 2005, could you feed it leading text about discoveries after 2005 and see if it hypothesizes the justification for those discoveries in the s…
STEM people love to bring up the sokal affair. the same STEM people also don't realize that many journals and conferences in STEM have been tricked by things like this (more specifically precursors using HMMs and etc). https://en.wikipedia.org/wiki/List_of_scholarly_publishing_s... edit: don't understand why i'm getting downvoted. is my comment not relevant to a post about the plausibility of abstracts generated by M…
On easy, 7 correct and 0 wrong was enough to tell me that yes, I can (I have been reading Nature for years though).
Still interesting!
5/5 on hard node, but it’s tough sometimes, I don’t actually know much about biology. But if you’ve played around with GPT before, you get better at spotting the subtle logical errors it tends to make. I wonder whether the ability to identify machine generated texts will become a useful skill at some point.
5/5 on hard node, but it’s tough sometimes, I don’t actually know much about biology. But if you’ve played around with GPT before, you get better at spotting the subtle logical errors it tends to make. I wonder whether the ability to identify machine generated texts will become a useful skill at some point.
Or you just train a machine to do it and then generate a bunch and have this second machine sort out any it thinks are machine generated.
5/5 on hard node, but it’s tough sometimes, I don’t actually know much about biology. But if you’ve played around with GPT before, you get better at spotting the subtle logical errors it tends to make. I wonder whether the ability to identify machine generated texts will become a useful skill at some point.
Or you just train a machine to do it and then generate a bunch and have this second machine sort out any it thinks are machine generated.
Earlier quoted context omitted.
Or you just train a machine to do it and then generate a bunch and have this second machine sort out any it thinks are machine generated.
You basically just described a GAN. Neat!