When ML models get more competent, ML capabilities researchers will have strong incentives to build superhuman models. Finding superhuman training techniques would be the main thing they'd work on. Consequently, when the problem is more tractable, I don't see why it'd be neglected by the capabilities community--it'd be unreasonable for profit maximizers not to have it as a top priority when it becomes tractable. I don't see why alignment researchers have to work in this area with high externalities now and ignore other safe alignment research areas (in pra...
I am strongly in favor of our very best content going on arXiv. Both communities should engage more with each other.
As follows are suggestions for posting to arXiv. As a rule of thumb, if the content of a blogpost didn't take >300 hours of labor to create, then it probably should not go on arXiv. Maintaining a basic quality bar prevents arXiv from being overriden by people who like writing up many of their inchoate thoughts; publication standards are different for LW/AF than for arXiv. Even if a researcher spent many hours on the project, arXiv moderato...
Strongly agree. Three examples of work I've put on Arxiv which originated from the forum, which might be helpful as a touchstone. The first was cited 7 times the first year, and 50 more times since. The latter two were posted last year, and have not been indexed by Google as having been cited yet.
As an example of a technical but fairly conceptual paper, there is the Categorizing Goodhart's law paper. I pushed for this to be a paper rather than just a post, and I think that the resulting exposure was very worthwhile. Scott wrote the original pos...
Here's a continual stream of related arXiv papers available through reddit and twitter.
I should say formatting is likely a large contributing factor for this outcome. Tom Dietterich, an arXiv moderator, apparently had a positive impression of the content of your grokking analysis. However, research on arXiv will be more likely to go live if it conforms to standard (ICLR, NeurIPS, ICML) formatting and isn't a blogpost automatically exported into a TeX file.
I agree that formatting is the most likely issue. The content of Neel's grokking work is clearly suitable for arXiv (just very solid ML work). And the style of presentation of the blog post is already fairly similar to a standard paper (e.g. is has an Introduction section, lists contributions in bullet points, ...).
So yeah, I agree that formatting/layout probably will do the trick (including stuff like academic citation style).
This may have been true four years ago, but ML researchers at leading labs rarely directly work on self-driving cars (e.g., research on sensor fusion). AV is has not been hot in quite a while. Fortunately now that AGI-like chatbots are popular, we're moving out of the realm of talking about making very narrow systems safer. The association with AV was not that bad since it was about getting many nines of reliability/extreme reliability, which was a useful subgoal. Unfortunately the world has not ... (read more)