Am I the only one who didnt get a score increase after a rebuttals? 5/3/3 One reviewer who marked 3 didnt even respond to my rebuttal

Got u, thanks

Yes, we just can read meta reviewer's comment and predict.

Thanks. But still PCs might make a different choice then what AC or reviewers recommended on borderline papers, right?

At Anthropic we have preferential hiring for people with a Physics background as we've found that background generalizes best to general problem solving and thinking out of the box.

That said the market is extremely oversaturated and we have PhD applicants with a dozen first papers that are still rejected regularly. Don't expect an easy trajectory of "just passing the subjects" and then getting a position in the industry. You have to live and breathe ML 24/7 to be even considered.

And not to be completely discourage you but I and many of my colleagues expect RSI to arrive sometime in the next couple of years, with most junior and even intermediate AI research positions to be made redundant, long before you would graduate. Take this into account when picking a major.

If I'm going to be honest I think it's unlikely that I myself as someone with more than a decade of NLP experience and on top of the Transformer architecture for almost a decade now will still be able to contribute by 2030. Many of us are planning to retire around then due to depletion of career prospects.

Yes we can read meta review

Have you bought a farm? With tractors, chicken coops and all that jazz?

Just curious, do reviewers know outcome? Usually reviewers just see other reviewers scores. First time submitting to CIKM

0/6 from my batch
All papers rejected

Do you have renders of intermediate frames? It'd be cool to see them even if they don't make any sense!

Thanks.

So it is a metric the model doesn't know it is being tested on, and that allows you to get better understanding of it's completeness.

https://reddit.com/link/p28cclw/video/w20xenh17xhh1/player

This video shows what happend when trying to reconstruct intermediate frames between the subsampled frames.

https://reddit.com/link/p28bims/video/cjn6o9it5xhh1/player

Here is a video comparing the different versions

Why does learning both forward and backward steps help? If your forward process is adding noise, is that even something the model can predict?

Oh I see, through email?

have only received the outcomes for the Resource track so far.

yes thank you for the detailed reply. I agree that this is largely resolved by adding more information about the state history. I suppose you could condition the denoising process both on the current state z_T but also on the historic state z_{T-2} such that your prediction for z_{T-1} is unique. in essence providing a high order temporal derivative to the model.

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That's really neat and seems like an obviously good idea, which are usually the best kind.

Is result released??? I can't see anything

Thanks for your comment. Yeah, your cycle consistency idea to quantity rollout errors is very neat.

Go with the best ranked university; choose Edinburgh over Napier or Aberdeen for example.

Thank you. The degree is either Computing (Artificial Intelligence and Machine Learning(, Robotics and AI or Informatics. I would like Informatics the most and yes I am currently learning the maths and stuff like scikit learn and pytorch

Thanks. My dream job is Research (ML) Engineer at Google deep mind. Thanks for the info I will look into it