Jun Li

This is part of a wider move across venues to adapt to AI-assisted writing and reviewing.

The near-term test is whether quality improves without pushing good surveys to closed venues or paywalls.

Authors doing legitimate reviews may need to plan for traditional peer reviews earlier in their workflows.

So filtering noisy reviews could raise the signal on Archive, but it also shifts effort to journals and conferences.

On the surface, this sounds completely valid.

I think it's probably a step they had to do.

The onus falls upon journals and conferences, though, which are limited.

So their resources are also limited.

So this might be a case of kicking the can down the road or saying, hey, we don't want to deal with it.

It should be on your side of things.

But I think what we need is a larger analysis and restructuring of the pipeline.

I think this is another example of how AI is moving things so quickly that the systems in place, the logistics of research pipeline needs to be adapted and there needs to be more options and things like that.

But it's good to see that this is a, we recognize the problem.

And while it may slow certain things down through our pipeline, it will overall probably be a good thing.

Yeah.

And this is definitely something that I would need to look into more detail for the process.

But from what I've seen so far, this wouldn't necessarily slow certain types of research papers that come out.

And at what stage?

I'm assuming something that is going to be like a Sakana example.

They're definitely going to release it in their own publications first or in, you know, in tandem.