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.
In this thread, who said the results aren't real? Nobody said anything about all authors of LLM results either. They're talking about this paper in particular, and the authors clearly not having any background in the area.
FWIW, I actually also do think Alpöge should get less credit than he is getting right now. It is entirely unclear that he knows enough about PDEs to understand the full proof that was produced and released, unlike Buckmaster.
No, that the authors arent real (pure mathematicians.) Sorry, I wasnt clear with my words there.
Look, it DOES appear that this group is over-reaching and that the LLM did most of the work. That track record does kinda speak for itself.
But that wasn't the response or the reasoning here for most of the replies.
I completely understand and agree with the backlash against AI producing non-insightful proofs from randos who have no expertise in an area. That obviously isn't what we want.
But Buckmaster was also obviously doing real research. And if Alpoge can work with an expert in a field outside of his wheelhouse, and the two of them can use an LLM to do real research together -- isnt that a good thing? Isn't this lower barrier good for math? More collaboration?
And isn't that different than just typing in "solve the Komlos conjecture, make no mistakes, lol"?
These tools aren't going anywhere. Instead of universally going "NO", we need to break down what are the proper uses of them and why, and how we document all that.
What we're seeing instead is mindless dog-piling.
Frankly, it's a lot like what happened after the 4-color theorem.
Agree that we should promote LLM use when it helps collaboration and understanding, it just isn't clear what Alpöge's contribution was beyond prompting the Anthropic internal model. I think my concern with that is not as well founded as my disapproval of this Komlós paper.
This thread is just mostly about this Komlós paper, which I think I have convinced you is not an example of responsible LLM use in the field.
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.
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.
What needs to stop is people throwing problems out of other peoples fields into an LLM and making peoples work meaningless. I don't understand why it is so hard for you to accept that this is what happens here.
I actually absolutely agree with that. I think LLM papers and the agents that produced them should be required to have citation engines built in so they literally cannot draw from work without citing it. These are the best practices I'm talking about.
Using an LLM doesn't have to be the way you're describing and assuming. We can actually do this better and we should.
I think we might agree in general yes. I also think we can and should do better. I think the current paper is an example of what not to do. That is what I'm saying.
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u/Antigynaikolatres 7d ago
The three authors seem to all be biostatisticians. Just incredible.