In deep learning a lot of papers end up only on arXiv, and authors don't bother (or need) to send it anywhere. Or even more, some seminal papers and up only on the author's page (e.g. one introducing GPT-2 https://openai.com/blog/better-language-models/). I am not a big fan of the latter, as it gives problems with long-term availability.
Of course, only corporate researchers can rely on not publishing in established journals - as their salary and position does not come from "publish or perish" metrics. Ironically, it means that there is more academic freedom in private companies than in academia.
Bell Labs in its heyday was still reputed to be publish or perish, or patent or perish, without any tenure system either. At my university, we had a previous Bell Labs researcher that said he had been pushed out. As a corporate researcher, there is still high pressure to output something.
Moreover, the correlation with acceptance and impact in existing, but not that high: https://medium.com/ai2-blog/what-open-data-tells-us-about-re...
Of course, only corporate researchers can rely on not publishing in established journals - as their salary and position does not come from "publish or perish" metrics. Ironically, it means that there is more academic freedom in private companies than in academia.