[psb217]

"if you haven't read them you also shouldn't cite them" -- this is wildly incorrect in an academic context. If I'm using ResNets, I should cite the original ResNet paper, even if I haven't read it. If I'm using Transformers, I should cite the original Transformer paper, even if I haven't read it. If my work is a direct extension of method B, and method B is a direct extension of method A, I should cite the source of A, even if I haven't read it.

You can't claim independence from past work simply because you didn't look directly at it. The job of an academic researcher is to know the landscape of relevant ideas, where they come from, where they're going, and to hopefully contribute a few new good ones.

Citation chains should extend back from your work, along a reasonable line conceptual inheritance, back to a reasonable point of origin. Schmidhuber has different definitions for both of these reasonables than the bulk of the ML research community, to a point that makes him difficult to satisfy.

[jasonhong]

It's worth pointing out that sometimes, some papers just become part of the general context of things and are no longer explicitly cited. Or people cite textbooks or general survey papers instead.

For example, take a look at Albert Einstein's Google Scholar profile. He's not the top cited physicist. Not even close. It's because other researchers don't explicitly cite his papers. https://scholar.google.com/citations?user=qc6CJjYAAAAJ&hl=en...

Same with Tim Berners-Lee and the World Wide Web. Imagine if his original paper were cited every time someone deployed a web site.

[inigyou]

You should read those papers then