One way to look at this is serious validation for your approach. Now, I'm not an academic myself – I know how it works, and that "first" is important, in that realm.

As others have said, acknowledging the concurrent research and mutual citations seems a reasonable approach forward.

I can totally relate. I basically also invented the U-Net architecture and had the paper on the review process when I learned about the Ronneberg paper. Plus he had a website and shared the code while my group was still debating how to license the code. Fast forward to today, U-Net as something like 50k citations and my paper about 500, which is still great and much more what I expected starting as a PhD student. But in hindsight also a bit disappointing knowing what I did and how much credit I got.

5 Is tricky because its desireable to add custom training sets to giant models, so folk will add anything that was banned. And open source copies of ultra powerful tools will only be a few years away.

Can you share your arXiv link?

I'm gonna be a little brusque, and say it sounds like they're strong arming you here to take some more credit, if you truly had your work in preprint before theirs it'd stay pretty firm in asking them to cite your work when theirs comes out since yours was in preprint first.

[removed]

I don't think that's a problem at all. Parallel publications happen all the time. What can happen is that you might have to cite them in the revision (if their work is already peer reviewed) or that they'll have to cite you in their revision (if their work is not yet peer reviewed).

I work in Astronomy, not in ML, but review first and arxiv later is how most people work in Europe. I typically don't find european arxiv papers that are not accepted for publication already. It's different for US papers. US groups are much more aggressive at pushing their work out, but that also means more people getting wrong information when the paper changes significantly in the review process.

Indeed! I’ve asked the main author if he’d like to meet up with me and discuss our research so hopefully it goes somewhere :)

>Haha good call. I’ve started a discourse with them now and they said that they’ll decide whether to cite my paper once both have been accepted somewhere and whether they like some of the video results I can show them. Promising stuff at least!

yup! Academia and research is really about the collaborations that get formed rather than one project. This might be more helpful to you than if it had not happened. Good luck!

Whats the right way to use arXiv?

A multilingual version of this would be nice

Haha good call. I’ve started a discourse with them now and they said that they’ll decide whether to cite my paper once both have been accepted somewhere and whether they like some of the video results I can show them. Promising stuff at least!

We are all individuals!

We are all individuals!

Publish also in ArXiv

The same with TV: Baird, Zworkyin and Farnsworth.

If they can automate huge chunks of super busy cargo harbors, they can automate valet parking...and they won't even need AGI for that. Hell, valet parking will likely become obsolete once full self driving is here.

People also didn't think AI will make artists obsolete...but here we are.

A good reviewer will know that parallel invention is not grounds for rejecting your paper. Neither is the amount of experimentation. If anything, it strengthens the paper because now we have two days points from independent sources. This is also an opportunity to collaborate with the other group

I wish my intuitions were so good that I could find research papers where someone did it and it kicked butt. You should take some time to appreciate your brain.

Yup! At least I know for the future now.

Thank you very much!

30% faster than the original TTTS!

We are providing the API at cost, i.e. $0.0005833/second.
We also provide $5 of free credits to try out the API. It currently costs $0.03/30words. Therefore, $5 ~ 160 API calls.

Based on your comment, its at par with replicate pricing. But, we will be faster with inference times & hence yielding micro-savings compounding over time

You are absolutely right. However, despite being open source, it requires a lot of time/effort/resources to get the tortoise text-to-speech synthesis working. Therefore, it's very difficult for a non-technical person to use, and for most developers looking to build applications on top it's a waste of time since they will have to reinvent the wheel to create an ML endpoint.

That is why we built this managed API on top for anyone to get started with testing the model / integrating TTTS quickly. Hope that helps?

We open-sourced our ML infrastructure for TTTS deployment so that others can contribute to make it faster, scale better or add features like easy fine-tuning with data.

> mention that this paper was submitted to CVPR in the comments

I think that publicly mentioning the arXiv preprint was submitted to CVPR is explicitly against CVPR policy. So I wouldn't do this second part of your advice.

I wouldn't make a big deal of when it was submitted (especially since you didn't upload it to arXiv like you should have). You can mention in passing that your paper is under review at CVPR. The important thing to note is that you spotted their work because it is similar to what you were working on and would be eager to cite each other as concurrent and talk to them about the work and future directions.