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I just stumbled upon a paper https://openreview.net/forum?id=HylxE1HKwS / https://arxiv.org/abs/1908.09791 with quite an interesting idea of training a single deep network that can be deployed at many efficiency configurations. But, what’s more “interesting” is the amount of self-citations in the paper. Seven of the cited publications had the third author’s name (which I assume is the PI). I feel that it is excessive. Correct me if I’m wrong. And the fact that this paper is heavily self-citing but isn’t acknowledging existing research that pursued similar direction (e.g., AuxNet, BranchyNet, IDK Cascades, Stochastic Downsampling, Anytime Neural Networks) is worrying.
What do you think of the self-citation trend (if there’s any at all) in machine learning research?
submitted by /u/TreeNetworks
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