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Grandiose claims, barely-readable and buzzword-saturated language, really weird experiment setup, lack of critical self-examination. These common features of re
by colllectorof 10y ago
Grandiose claims, barely-readable and buzzword-saturated language, really weird experiment setup, lack of critical self-examination. These common features of recent AI research papers begin to annoy me. Especially when it's seen in corporate research, where (supposedly) results should be more important than a kind of lingual tribalism seen in academia. Is it really that hard to produce a human-readable description of the architecture and put it in a particular place of the paper instead of spreading them all over? Also, it took me quite a while to understand what the heck they were measuring (and how) in the first place.
- feylikurds 10y agoTHIS!
- daveguy 10y ago> Is it really that hard to produce a human-readable description of the architecture and put it in a particular place of the paper instead of spreading them all over? That would allow easier reproducibility, which is the opposite of the goal for papers that come out of industry. This is the purpose of industry papers (in order of importance): 1) Avoid sufficient clarity such that competing companies could reproduce the work. 2) Brag about the company's capabilities such that it increases interest from potential customers. 3) Maintain just enough scientific rigor and clarity that it is still publishable. 1 is generally top priority. 2 is the goal. If 1 prevents 3 then they just call it a white paper and publish only to arxiv or on their website. That way you still get exposure for 2 without compromising 1.