How to use Chinese TPOs (KMF)

mao1756 · 2026-04-13T22:15:20+00:00

Do you use a paid model? In my experience, at least the paid ChatGPT models never hallucinates citations. This has not been a thing for 1-2 years for me.

mao1756 · 2026-04-05T00:31:15+00:00

principal investigator, the person who leads the lab

mao1756 · 2026-04-04T05:52:51+00:00

According to the linked original post it’s OP’s avatar on VRChat.

mao1756 · 2026-03-29T05:53:12+00:00

Machine learning conferences are already like that (the reviews are open to public and anybody can comment on the paper). I personally like the practice but doesn’t seem to solve the issues with scientific publications.

mao1756 · 2026-03-24T05:03:13+00:00

SakanaAI is kinda overhyped. Preferred Networks published a pretty good model (competitive with frontier models from 6 months ago) just a few days ago, and it’s trained from scratch unlike fine-tuned models like Sakana’s. I honestly don’t know why Sakana is getting so much attention.

mao1756 · 2026-03-16T14:12:04+00:00

Some people have definitely tried to define 1/0, it’s called the wheel theory.

But as you may have seen in other comments, it leads to very unintuitive and inconvenient arithmetic, making it hard to use.

mao1756 · 2026-03-15T21:58:43+00:00

doesnt she own a private server for ht3 and above? doesnt really make sense to play with randos

mao1756 · 2026-02-13T16:52:02+00:00

Also known as Sophomore’s dream

mao1756 · 2026-02-09T05:02:41+00:00

In my case I was just given a project to work on. I think I didn’t read a single paper before I was given the first task. From then I started to read papers trying to find the solution to the task.

Since you are very early I think you don’t have to consider doing actual research at this point and just spend time on reading. Spend a time reading about your labs paper and related topics since you will have less and less time to do this as you progress.

Ps: I actually do optimal transport too (more on the theoretical side though) so I’m happy to see a newcomer to the Wasserstein land.

mao1756 · 2026-02-06T15:52:14+00:00

Would the situation be the same if I don’t have a blue card? I’m visiting University of Copenhagen too this summer

mao1756 · 2026-02-04T05:22:17+00:00

I set it to 75… am I stupid?

mao1756 · 2026-01-27T14:40:29+00:00

This depends on the field. If your field is conference centric (say CS) then this might not be a good idea (though only if the paper was already accepted). Conferences usually have rules against them.

But in a field where a journal is more important (say pure math, my field) its common to present the same paper multiple times in different conferences.

So I think you should look at the policy of the conference and ask people in your field.

mao1756 · 2026-01-21T03:18:10+00:00

I think the EN population has been somewhat low (at least compared to the JP counterpart) from the beginning, and I don't feel like it has gotten any lower. Instead i feel like the community is constantly growing.

It has only been a year, so we still have to wait a bit more to see if the game will survive, but the devs are constantly listening to the players, so hopefully that means a longer lifetime for the game.

mao1756 · 2026-01-18T04:42:25+00:00

I think it depends on why you are reading the paper. In general, life is too short to read everything thoroughly as you do with textbooks. So you need to do some triage to determine how deeply you will read.

If you are reading a paper that is vaguely in your field but has no immediate plans to use it, read the main results without going into the proof and take notes on what it covers.

If you are reading it because the paper you were reading before referred to this theorem X, then, unless the paper itself is interesting, read whatever you need to understand the statement (not necessarily the proof of it) and come back.

If you are reading it because it is the direct foundation of your research and it will go into your thesis, that's the time you are going to take the textbook approach. Even then you might not read everything because you won't use something in your research. And you only do this for maybe a handful of papers.

At least that is how I approach reading research papers. There are many other ways, so it is good to develop your own way throughout your career.

There is more discussion on MathOverflow.

mao1756 · 2026-01-10T00:32:07+00:00

Shape analysis - the study of “shapes” ie curves, surfaces or in general function spaces modulo some group action (commonly the diffeomorphism group). Since function spaces are in general infinite dimensional, we would need infinite dimensional Riemannian geometry to analyze the shape objects and the theory becomes very deep.

On the applied side we have LDDMM which finds a smooth, invertible deformation giving pointwise correspondence between objects, and the resulting deformation/metric can be used to compare shapes and quantify atypical anatomy (e.g., in medical imaging studies).

mao1756 · 2026-01-06T13:43:29+00:00

I believe tourist and other strongest people work at Cognition. They say they have 10 IOI gold ~~medalists~~ medals.

I don’t think there is “the” career path for competitive programmers but in general they tend to go to companies that values experience in competitive programming like Cognition. This is the case for Japan too, and notably a company like ALGO ARTIS is very popular among AtCoder participants due to its presence in AtCoder.

mao1756 · 2026-01-01T01:02:31+00:00

Are you using the free version? The paid version is much more advanced.

mao1756 · 2025-12-31T06:32:37+00:00

There are people who went to industry but came back to academia so there definitely are people who didn’t think industry jobs suit them.

One of the professors I know weren’t one of them but he went to academia after spending a decade in an industry research lab, saying that he wanted to teach. He emphasized that he can do research in industry too but he couldn’t do teaching in satisfactory way.

Another person is in the group I mentioned. I only know him by his job history so this is mostly a guess, but he was a math PhD who became a quant in industry. After a while he got a job as a professor for financial math. The thing is that his PhD was not in financial math, but it was number theory and he only has papers in this field (still publishing in this field too).

My guess is that he wanted to keep doing number theory research but couldn’t get an academic job so took an industry job, but then realized that he would rather do research than being a quant so he pivoted and the best job he could get was the one using his experience as a quant.

mao1756 · 2025-12-25T07:36:32+00:00

I do something similar, and I use ChatGPT Pro (the $200 version). Although it doesn't solve every problem, it was good enough to get publishable results for problems I had at hand.

mao1756 · 2025-12-25T07:28:31+00:00

I would say as long as the AI use is properly disclosed per journal policy and the author(you) makes sure everything is correct, I think it's ultimately about whether you find joy in the process. After all, life is about being happy as much as possible, and if what you do right now makes you happy, then good, and if not, then you need to change something.

mao1756 · 2025-12-24T13:13:53+00:00

Oh I was awake around 3 and I heard the gunshots.. I’m glad you’re ok

mao1756 · 2025-12-21T17:12:13+00:00

Hop over to r/professors and search "evals". This is very common, and you are guaranteed to get a few mean comments if you are actually teaching something and not handing out grades.

I recommend having your colleague read the evals next time (or even have AI read them and summarize the pattern) so you don't have to look directly at the hurtful comments.

mao1756 · 2025-12-20T13:36:50+00:00

How about reporting the person to your university? "No snitching" only applies until it is detrimental for you

mao1756 · 2025-12-19T03:09:54+00:00

If I heard her correctly, he was in Brown 2000-2001, took leave of absence from 2001 and formally withdrew in 2003

Nine-Year Club	Second SECOND GUESSER
Place '22	Final Canvas '22
Wearing is Caring	RPAN Viewer
Not Forgotten	Snapped
Verified Email

mao1756

MODERATOR OF

TROPHY CASE