[chriskanan]

I've observed this in multiple AI niches. In some cases I've emailed people saying they ignored very similar work and failed to cite it, and in at least some cases, they were apologetic and said they would update the arXiv version. Although of those times, they do that 50% of the time. Kind of tells you that the reviewers at top AI conferences themselves aren't that familiar with the breadth of the literature.

[michaelmior]

To be fair, there are so many publications in fields such as AI that it's really hard to stay on top of things, sometimes even within your own specific subarea. I'm not saying that to give reviewers a total pass, but I think it's reasonable that sometimes a group of reviewers might miss a relevant paper.

[generic92034]

Yes, there are just too many publications, even with a very narrow focus. I am reminded of this article: https://slatestarcodex.com/2017/11/09/ars-longa-vita-brevis/

[bsdpufferfish]

Of course they aren’t familiar with the literature. Most of the papers rediscover existing math and physics in a worse way (harmonic analysis, etc)