I can see how citations can get very complex for the purposes of scientific credit, traditionally there's a self-policed aspect to it in every academic community; however, in this century as advanced research gets more complex and globalized, it might be time for a more rigorous and neutral process of doing so.
Schmidhuber is only the worst of many abusers of the citation system. Everyone knows that anonymous reviewers are more likely to approve of people who cite their work. Someone is politically powerful? Better cite their paper, even though you don't really think it's a good paper and you didn't use it.
Schmidhuber is cited far more often than he should be, because people just don't want to deal with this crap, and the cost of sticking in one more citation is very low.
The audacity of deciding on behalf of readers whether information is valuable to them when publishing an academic paper is quite an interesting concept to me.
I'm not published in journals, but I do have a "professional" writing background. There's only a few ways I can imagine to read into your statement. Either you think you're above citation, or so much smarter than the reader you're qualified to decide on their behalf whether it's relevant, or simply hiding it for nefarious reasons.
Any of these options, or even the perception of them, is precisely the type of behavior fostering anti intellectualism and prejudice for academia.
It's also quite ironic you repeatedly mention "politics" while your entire argument seems to hinge on seeking to deny empowering further those already in power. Isn't that exercising political capital?
These are very good points.
> ... the worst of many abusers of the citation system.
Is this ad hominem argument by user "lacker" meant to distract from the omissions of the awardees Bengio, Hinton, and LeCun? Especially the first two got tons of citations for work that should have credited Schmidhuber's lab: the analysis of vanishing gradients in neural networks, the principle of generative adversarial networks, attention in neural networks, distilling neural networks, speech recognition with LSTM neural networks, self-supervised pre-training, and more.
The disputes with LeCun are more recent and of lesser magnitude IMO.
The reason that this is not the norm in academia is because there is a substantial number of researchers who care very, very much about academic integrity and even more so about getting their work properly recognised, just like good old You_again.
Btw, "everyone knows" is a running joke in Game of Thrones, it's what the Dothraki always say to show that they're pre-scientific barbarians who believe whatever they like, or at least that's how I get the joke.
But as I said before, we should take the long view. Globalized scientific research ought to have a more neutral way of assessing citations. The 20th century way of doing it may not be the right way any more. I don't see anyone else suggesting a problem of this scope.
You haven't even read the paper, have you? Otherwise you'd see that it's Hinton and Bengio who are cited far more often than they should be. Just look at disputes B1, B2, B5, H2, H4, and H5 to see how they republished parts of his work again and again without citing it. No honest scientist can approve of something like that.
Another aspect that makes it difficult is that different people even in the same field use different terms for the same thing. As an example, engineering optimal control folks like to optimize cost functions, economists might refer to that as the utility instead, and RL folks like to use rewards (which is just a negative of a cost and functionally equivalent). That makes it difficult to run a search. I’ve come across a whole slew of new papers to read on topics just by changing out key terms for synonyms.
A reviewer may suggest other works to include in your discussion. Sometimes the recommendations are appropriate, other times it’s a backhanded way to fish for citations and the works suggested aren’t actually relevant. I would say harping over not including one is poor form unless it is so similar that is important for you to explain the novel aspect in your paper.
> BTW, I committed a similar error in 1987 when I published what I thought was the first paper on Genetic Programming (GP), that is, on automatically evolving computer programs[GP1][GP] (authors in alphabetic order). At least our 1987 paper[GP1] seems to be the first on GP for codes with loops and codes of variable size, and the first on GP implemented in a Logic Programming language. Only later I found out that Nichael Cramer had published GP already in 1985[GP0] (and that Stephen F. Smith had proposed a related approach as part of a larger system[GPA] in 1980). Since then I have been trying to do the right thing and correctly attribute credit.
Source: https://people.idsia.ch/~juergen/deep-learning-miraculous-ye...
He put you through the wringer for not citing him in the announcement of the title?