The lede is buried deep in this one. Yeah, these dumb LLMs got bad training data that persists to this day, but more concerning is the fact that some scientists are relying upon LLMs to write their papers. This is literally the way scientists communicate their findings to other scientists, lawmakers, and the public, and they’re using fucking predictive text like it has cognition and knows anything.
Sure, most (all?) of those papers got retracted, but those are just the ones that got caught. How many more are lurking out there with garbage claims fabricated by a chatbot?
Thankfully, science will inevitably sus those papers out eventually, as it always does, but it’s shameful that any scientist would be so fatuous to put out a paper written by a dumb bot. You’re the experts. Write your own goddamn papers.
In some cases, it’s people who’ve done the research and written the paper who then use an LLM to give it a final polish. Often, it’s people who are writing in a non-native language.
Doesn’t make it good or right, but adds some context.
Sure, and I’m sympathetic to the baffling difficulties of English, but use Google Translate and ask someone who’s more fluent for help with the final polish (as a single suggestion). Trusting your work, trusting science to an LLM is lunacy.
And before they were using neural network approaches they used statistical approaches, which are subject to the same errors as a result of bad training data.
It might be hard for them to find someone who is both fluent in english AND knows the field well enough to know vegetative electron microscopy is not a thing. Most universities have one general translation help service and science has a lot of field-specific weird terms.
There is a huge difference between asking a LLM “ translate the quick brown fox jumped over the lazy dog” and “ write a sentence about a fox and a dog” when you ask it to translate you can get weird translation issues like we saw here but you also get those sometimes with google translate but it shouldn’t change the actual content of the paper
Have you asked an LLM to translate anything bigger than a few sentences? It doesn’t have enough contextual storage to keep a whole paper “in mind” and soon wanders off into nonsense.
oh yea,not to mention alot of papers tend to be low quality before the AI was used, ive been hearing people are writing dozens of papers just to fluff up thier resume/cv. it was quanitity over quality. i was in an presentation where the guy presenting thier research wrote 40+ papers just to get hired a university somewhere.
The lede is buried deep in this one. Yeah, these dumb LLMs got bad training data that persists to this day, but more concerning is the fact that some scientists are relying upon LLMs to write their papers. This is literally the way scientists communicate their findings to other scientists, lawmakers, and the public, and they’re using fucking predictive text like it has cognition and knows anything.
Sure, most (all?) of those papers got retracted, but those are just the ones that got caught. How many more are lurking out there with garbage claims fabricated by a chatbot?
Thankfully, science will inevitably sus those papers out eventually, as it always does, but it’s shameful that any scientist would be so fatuous to put out a paper written by a dumb bot. You’re the experts. Write your own goddamn papers.
In some cases, it’s people who’ve done the research and written the paper who then use an LLM to give it a final polish. Often, it’s people who are writing in a non-native language.
Doesn’t make it good or right, but adds some context.
Sure, and I’m sympathetic to the baffling difficulties of English, but use Google Translate and ask someone who’s more fluent for help with the final polish (as a single suggestion). Trusting your work, trusting science to an LLM is lunacy.
Google translate is using the same approach like an LLM.
https://en.wikipedia.org/wiki/Google_Translate
https://en.wikipedia.org/wiki/Neural_machine_translation
So is DeepL
https://en.wikipedia.org/wiki/DeepL_Translator
And before they were using neural network approaches they used statistical approaches, which are subject to the same errors as a result of bad training data.
Check the results though. Google translate is far far better at translation than a generic LLM.
It might be hard for them to find someone who is both fluent in english AND knows the field well enough to know vegetative electron microscopy is not a thing. Most universities have one general translation help service and science has a lot of field-specific weird terms.
That’s why he said start with Google Translate. Because Google Translate isn’t giving gibberish like vegetative electron microscopy.
Adding extra polish like nonsense phrases. Nobody is supervising it then.
They were translating them not actually writing them like obviously it should have been caught by reviewers but that’s not nearly as bad
Translating them…otherwise know as rewriting the whole paper.
There is a huge difference between asking a LLM “ translate the quick brown fox jumped over the lazy dog” and “ write a sentence about a fox and a dog” when you ask it to translate you can get weird translation issues like we saw here but you also get those sometimes with google translate but it shouldn’t change the actual content of the paper
Have you asked an LLM to translate anything bigger than a few sentences? It doesn’t have enough contextual storage to keep a whole paper “in mind” and soon wanders off into nonsense.
Google translate is a different beast.
In the future, all search engines will have an option to ignore any results from 2022-20xx, the era of AI slop.
oh yea,not to mention alot of papers tend to be low quality before the AI was used, ive been hearing people are writing dozens of papers just to fluff up thier resume/cv. it was quanitity over quality. i was in an presentation where the guy presenting thier research wrote 40+ papers just to get hired a university somewhere.
Its the immediate takeaway i made from the headline, so i dont feel like its buried deep
It’s not mentioned at all in the article, so what you inferred from the headline is not what the author conveyed.
Ah, i admit i didnt read it, because the headline and the implication of AI being an issue in academia wasnt exactly news to me.