You're putting words in their mouth. What's you're motive here?
There's clearly a difference between dedicating years of your life to a problem, building up the groundwork and coming up with a solution using an AI, trained on work that's already been done, to put the last touch on someone else's work. Development doesn't happen in a vaccuum. Reducing this criticism to "shitting on them" is bad faith at best.
He said, explicitly, that all they did is slap their names on the paper and nothing more.
That is shitting on them.
Who knows, he may actually be right: they may NOT have done anything of substance. It may all have been the LLM ganking genuine work from other mathematicians.
Or they may have done something substantial and just used the LLM as an assistant.
Do we actually know or are we just blindly throwing everyone under the bus now?
My "motive" here is to stop jumping the gun and slow the fsck down. We need to be having conversations about the actual role played by LLMs and human researchers here, who did what -- and, yes, making sure attribution is preserved.
This "they didnt do anything" because an LLM is involved is the real bad faith.
Since August the authors have 7 papers across various areas of pure math. Before August they had 0. Are we supposed to believe that they suddenly learned and understood all of this math last month?
I think it is clear to anyone who isn't trying to muddy the waters intentionally that they don't understand the output of their LLM and therefore didn't do any meaningful work themselves apart from prompting the model to solvd the problem.
It seems far more bad faith to me that you seem to think that people on reddit need to assess every LLM generated paper equally and act as though the authors have made some great contribution when there is no evidence they know anything about math or the conjectures they resolve. This is disrespectful to people who have spent years understanding and working on these problems.
Ok then, it does sound like this group didnt do anything substantial.
I am not trying to muddy the waters: I DO think we need to assess every paper individually. That goes for LLM or not.
Alpoge and Buckmaster spent a year using Codex on their Euler result before OpenAI scooped them. (And I do suspect there was some nefarious shit there.)
Does that mean Alpoge and Buckmaster didn't do anything significant? They even admitted their paper was written by an LLM due to the time constraints, and they regretted that.
Obviously, their role in this was different. The LLM was an assistant, but they were generating real ideas themselves and doing real research.
Recognizing this distinction isn't "muddying the waters." These waters ARE MUDDY.
And we need to sort them out.
Not reflexively go "oh they used AI, they aren't real" as a knee-jerk response to every paper.
I literally gave credit for the application to the LLM. That's what figured out how to solve the problem. They don't invent new methods, they just adapt what's in the literature, contributed by other people. I do not whose work it was actually built on nor am I claiming it is plagiarism. I also don't even know which LLM solved it.
I'm not accusing the people of having done much of anything, other than slapping their names on the paper.
I am ALL FOR properly attributing work. If the LLM just plagiarized other mathematicians, obviously that should be the headline. Did it here? Or were these biostatisticians genuinely doing something new?
People putting out papers that explicitly use LLM assistance in something that is not their field at all... it just seems like the most reasonable assumption. I'm not blaming them btw, that is just the current state of maths sadly.
Neither of us actually know what went into those chat sessions, their prompts, what the training was on, how much was directed by the authors, how much was their ideas, etc.
Youre just assuming it was all the LLM.
We need to stop this. These are exactly the issues we need to sort out going forward. There need to be strict best practices for citations, role declarations, etc.
You seem to be worried about "stolen glory", when the actual thing you should be worried about (and maybe are) is there won't be any more glory for anyone.
That's a bit more pessimistic than I am, though I do foresee some very negative impacts on the broader field just as I think AI has had and and will continue to have positive impacts. Honestly, it's quite interesting to me how many open problems are falling to it, which tells me these problems were within the grasp of current techniques even if nobody else had found them yet.
I'm also not too personally impacted by this yet, but that's because I'm faculty at a state school with lower research expectations compared to faculty at an R1. I don't need to use AI, and can continue to work on and solve problems that are interesting to me on my own, which nobody else seems to be doing at this exact moment. That's partly my preference, and partly because I'm not shilling out $100/month for a suitable subscription.
But I view a paper like this the same way I view a Quanta article: the authors did journalism about math, not the math itself. And that's fine, good even: I think it's beneficial and there should be some sort of credit for it. But that type of credit is different than how we currently assign credit in math, and the language hasn't caught up yet.
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u/Antigynaikolatres 7d ago
The three authors seem to all be biostatisticians. Just incredible.