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by YeGoblynQueenne
1615 days ago
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This is not the case in computer science and particularly machine learning, especially in recent years. You'll find many papers where a majority of references are to preprints that stay preprints for ever. You'll also find many papers that have hundreds of citations, all while remaining preprints forever (and many of those citations are from forever-preprints themselves). In machine learning, for the most part, arxiv is used to avoid peer-review. Or a way to "publish" work that has been rejected by a peer-reviewed publication, of course. And to be more cynical, it's also a convenient source of references to pad up a Related Work section and make it look like incremental work is part of a growing body of groundbreaking new work. /jaded Edit: well, I'm not just being cynical. The fact that everyone can put their half-baked papers on arxiv means that the 90% of work that is crap, per Sturgeon's Law, is now a much bigger quantity than ever before and one must sift through reams and reams of crap before finding work that has any meaningful results to report. Again, that's the case in machine learning specifically. I don't know about other fields. |
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Arxiv only lacks the initial quality filter by peer review.
I'm also working in the field of machine learning. In those niche fields I work more specifically (speech recognition), I can usually still get a lot out of Arxiv-only papers. I can pretty easily see the main idea and see if there is some usefulness in the paper or not w.r.t. my own research e.g. by good experimental analysis. In don't really feel overwhelmed in the amount of papers. I don't really see the problem.