Librarian: Get links to references and Bibtex for papers on arXiv(fermatslibrary.com)
fermatslibrary.com
Librarian: Get links to references and Bibtex for papers on arXiv
https://fermatslibrary.com/librarian
6 comments
Can read your browser history... no thanks.
Chrome only (it's an extension) :(
Perhaps something can be done to collapse the buttons so they don't interfere with reading in zoomed mode. Useful tool by the way.
Seems useful.
However, I tried on several arXiv papers, and on all of them when clicking on references I get a "Sorry! We couldn't find the references for this paper. This paper might have been posted recently. Try again later."
(on chrome 59.0.3071.115)
However, I tried on several arXiv papers, and on all of them when clicking on references I get a "Sorry! We couldn't find the references for this paper. This paper might have been posted recently. Try again later."
(on chrome 59.0.3071.115)
I get this too. Haven't been able to get references to work for a single paper yet.
What's the point of referencing arXiv? They're supposed to be preprints or non-peer reviewed papers. Other than for re-using some of the text/images, the citations to arXiv papers won't/shouldn't be accepted by peer-review committees.
Something on arXiv can have had more "peer-review" than something that made it past 3 reviewers for a normal publication if it has been discussed a lot.
Also, not everything cited has to be properly published. If you base an argument on a finding from a source, then yes, but e.g. but descriptions of approaches, ideas, ... are things that can be cite-worthy while not requiring the "fact-checking" peer review provides.
It's an interesting balance: On the one hand, it's bad if stuff that just was published as a preprint is treated as established (which seems to be partially the case in ML right now), on the other hand not referencing good material just because it "doesn't look scientific enough" also doesn't help anyone. (In some parts of computing, it seems like academia is toying with stuff industry has tried and discarded years ago, but that isn't acknowledged because it hasn't been published in a nice citation. It's fine to do work to validate that, but totally ignoring it is weird)
Also, not everything cited has to be properly published. If you base an argument on a finding from a source, then yes, but e.g. but descriptions of approaches, ideas, ... are things that can be cite-worthy while not requiring the "fact-checking" peer review provides.
It's an interesting balance: On the one hand, it's bad if stuff that just was published as a preprint is treated as established (which seems to be partially the case in ML right now), on the other hand not referencing good material just because it "doesn't look scientific enough" also doesn't help anyone. (In some parts of computing, it seems like academia is toying with stuff industry has tried and discarded years ago, but that isn't acknowledged because it hasn't been published in a nice citation. It's fine to do work to validate that, but totally ignoring it is weird)
At least in math, that is just untrue. It can be years from when the first preprint comes out to when it's actually published. If everyone waited around for the official publication, nothing would ever get published. Journals are pretty pragmatic about it.
That doesn't make sense. I can publish anything on arXiv, and then refrence that in an academic journal, from what you're saying. That cannot and should not be how proper peer review happens. The delay in publication of math journals cannot be a reason to skip the proper peer review process!
It really depends on what you're using citations for. Peer-reviewed papers don't necessarily need a transitive property where they only cite other peer-reviewed papers (which only cite... etc.). Norms vary by field, but in most fields, it's always been acceptable to cite various kinds of non-peer-reviewed literature, such as technical reports. Even popular press articles or blogs are fine, as long as they're cited appropriately, not to back up critical claims. Ultimately the single paper under review is peer-reviewed for whether it demonstrates its own claims, and that depends in part on the reviewers judging whether it uses citations appropriately, meaning that it can cite anything it wants, as long as it doesn't cite things to demonstrate claims that the citation can't really support.
In mathematics my impression is that citing arXiv papers is usually done appropriately. If a surprising proof of a longstanding open problem was recently posted on arXiv, people won't usually cite it as authoritative right away. Instead a citation will be worded with something like "a recent claimed proof by so-and-so...", making it clear that it's still preliminary and not to be treated as a sure thing yet (how strongly to add this caveat is a bit of a judgment call).
As a reviewer that's usually what I look for. If someone cites an arXiv paper (or tech report, or even blog post) to give context, to credit other teams who are doing related work, to point out alternative approaches that the current paper isn't investigating, etc., that's perfectly fine. Those are more like informational "see also" citations. If a paper cites an arXiv preprint as authoritative evidence of something that is really critical to the current paper itself being correct, then yes, that's where it can be more iffy and I'd ask the authors to either qualify that claim more, or bolster it with another more solid citation. There is a little bit of a problem with this currently in machine learning, where some people make overly bold/general claims in arXiv preprints that their methodology/data can't really support, and other people sometimes cite these claims a bit too credulously. Important to push back on, but not to the extent of banning arXiv citations.
In mathematics my impression is that citing arXiv papers is usually done appropriately. If a surprising proof of a longstanding open problem was recently posted on arXiv, people won't usually cite it as authoritative right away. Instead a citation will be worded with something like "a recent claimed proof by so-and-so...", making it clear that it's still preliminary and not to be treated as a sure thing yet (how strongly to add this caveat is a bit of a judgment call).
As a reviewer that's usually what I look for. If someone cites an arXiv paper (or tech report, or even blog post) to give context, to credit other teams who are doing related work, to point out alternative approaches that the current paper isn't investigating, etc., that's perfectly fine. Those are more like informational "see also" citations. If a paper cites an arXiv preprint as authoritative evidence of something that is really critical to the current paper itself being correct, then yes, that's where it can be more iffy and I'd ask the authors to either qualify that claim more, or bolster it with another more solid citation. There is a little bit of a problem with this currently in machine learning, where some people make overly bold/general claims in arXiv preprints that their methodology/data can't really support, and other people sometimes cite these claims a bit too credulously. Important to push back on, but not to the extent of banning arXiv citations.
Same in some parts of astrophysics. The real peer review is social, you review when you cite so to speak, if you cite garbage then your work turn into garbage, so.... journal peer review is just an after-thought to collect points for funding and hiring bodies, it is not the real validation of research.
Not to mention I know examples of respected journals in the field letting total crap through (not opinion, total misapplication of statistical theorems) so the journal stamp of approval isn't everything.
Arxiv is not ideal, but I refuse to think going back to journals as gatekeeper is a step forwards. That would be a step backwards. Some sort of distributed social network peer review of arxiv papers, and having points scored there that count as the review for for papers for funding bodies etc would probably be best. The journal model is outdated and charging too much money to provide little value (I mean, they just coordinate the review process, a piece of software could do the same coordination).
Not to mention I know examples of respected journals in the field letting total crap through (not opinion, total misapplication of statistical theorems) so the journal stamp of approval isn't everything.
Arxiv is not ideal, but I refuse to think going back to journals as gatekeeper is a step forwards. That would be a step backwards. Some sort of distributed social network peer review of arxiv papers, and having points scored there that count as the review for for papers for funding bodies etc would probably be best. The journal model is outdated and charging too much money to provide little value (I mean, they just coordinate the review process, a piece of software could do the same coordination).
The arXiv _is_ moderated. If there's something wacky the moderators tend to ding it.
Irrelevant since as I understand it moderators only weed out papers that don't even have the appearance of on-topic research papers; that does nothing to ensure preprints on arXiv are trustworthy.
In addition to what others have said, there are lots of reasons to cite something that don't need that work to be correct. You cite works that inspire yours, even if they're not peer-reviewed. You cite works that ask questions you answer, as evidence that the problem is worth addressing. You cite papers that are works in progress but are related to what you are doing and are useful to give a reader background. Sometimes you intentionally cite mistaken work specifically so that you can correct it.
In CS, it also occasionally makes sense to cite an arXiv paper if it hasn't been accepted in a peer-reviewed publication. It's still helpful to acknowledge that you're aware of related work that exists regardless of what form it's been published in.
It is common practice to cite things other than peer-reviewed papers (at least in math). There are even citations for "private communication", usually meaning a personal email or conversation.
The arXiv of the future will not look like the arXiv https://www.authorea.com/users/3/articles/173764-the-arxiv-o...