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by ironSkillet10 hours ago |
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upvoteby robrenaud6 hours ago|
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It's cool that it proves that a bunch of vectorized outputs from an unknown embedder on an unknown dataset is in no way private, because of this ability to reverse engineer the embedder.

I talked to the author at his poster session at neurips and was able to get the gist, though I had read a lot about the platonic representation hypothesis, and this was one of my top 10 favorite papers in the conference.

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upvoteby 2 hours ago|
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upvoteby wging4 hours ago|
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They link to their code on GitHub - see footnote 2 on page 2. I don't see it linked anywhere else, which makes it easy to miss. https://github.com/rjha18/vec2vec/
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upvoteby Nail26807 hours ago|
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It isn't a maths paper, so the conventions are different.
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upvoteby adastra226 hours ago|
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This isn’t math. The exposition IS the details.
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upvoteby rhelz10 hours ago|
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You are not wrong. But this has by no means proven its up to the standard of being publishable in a machine learning journal. Its on arXiv.org, which, lets face it, at the end of the day is a vanity press.
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upvoteby contubernio5 hours ago|
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Calling the arxiv a vanity press shows you aren't a researcher. In math and physics all the best stuff is on the arxiv and the general level is well above the level of most journals. Journals mainly serve as accreditation and many are basically mediocre - the review process resta more value than it adds overall.
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upvoteby canjobear8 hours ago|
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It was accepted to NeurIPS.
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upvoteby odyssey79 hours ago|
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The pace of things is moving along so rapidly right now, I’m not sure that waiting for peer reviews is always a wise move. Doubly so if there’s a paywall; why limit your article’s impact by placing it where practitioners’ agents might not be able to access it? The rapid progress right now is challenging for conventional academic processes.

If the value of the paper is difficult to independently verify, for example, if it depends on the credibility of the author, then the academic ritual can add something. If it’s a mathematical result, one that can be automatically verified, or a machine learning technique that anyone can try with Claude code reconstructing it for them, this sort of pre-print publishing model is advantageous.

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upvoteby rhelz9 hours ago|
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// why limit your article's impact //

Because...science? It's not science until it passes peer review.

I'm not advocating that everybody stops posting to arXiv, and I'm not saying you can't find good stuff there. I'm just saying, it's a vanity press, there is absolutely no guarantee of the paper's quality.

And being published by a famous professor from a prestigious university is also no guarantee. If we've learned anything from the non-reproducibility crisis, it is that a paper's origin story is no guarantee.

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upvoteby Xmd5a1 hours ago|
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> It's not science until it passes peer review.

You mean Robert Maxwell's quasi-monopoly on scientific publications ?

https://www.theguardian.com/science/2017/jun/27/profitable-b...

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upvoteby anon482935 hours ago|
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Then again neither is peer review. Reproducing research is the only way to prove reproducibility and thereby lend credibility to the claims.
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upvoteby efavdb9 hours ago|
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At a minimum posting to arxiv gives others a standard way to cite the work.
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