Once upon a time, I was in condensed matter physics. I was (and remain) interested in a very specific niche within that, and I read a small handful of the papers that were published each week. I’m not actively researching or publishing anymore so I cap this to one or two per month now, and mostly scan over them to see if anything piques my interest.
I was still interested in condensed matter as a whole, at the time, and attended group seminars once a month to see what other people were currently excited about - there wasn’t any hope of me reading a cross section of all condensed matter papers because there is far more published per week than I’d be physically able to even glimpse at, and most of it is stuff I don’t understand or particularly care about.
I was likewise interested in physics as a whole, and twice a year I’d attend a departmental seminar and see what people in the entire department were interested in. Most was far over my head, but it still directed me to a small handful of papers that I’d read for the hell of it. Of course, I couldn’t do this without first hearing people review the research. There’s far more published per day in physics as a whole than I could read in a year, and most of it I’d find unrelatable and uninteresting.
I guess where I’m going with this is that anyone with a specific interest is already reading papers. It’s their job. Anyone with a general interest would find actively pursing paper hunting to be a waste of time with a ridiculously bad signal to noise ratio. Instead, they should use channels that align closely with their own interests, through which they can get recommendations to read papers from the aforementioned specialists who have already filtered out much of the noise themselves. At that point, they should actually read the resulting papers.
There is another trick, though, and that’s to find an individual who publishes two unrelated pieces of work that you find interesting, then read their work and maybe those of their coauthors. Be careful, though, because this is a slippery slope to specialising, after which you’ll find yourself back at the point where you don’t aren’t following 99.9% of the stuff you wanted to follow in the first place.
Honestly many papers are written in a way that's hard to approach and difficult to understand unless you're prepared to reread them a few times.
You're better off just getting your science news from actual science communicators and not the raw source.
I probably averaged 20 a week back in March when open source AI was booming in the wake of Llama and on the heels of GPT-4.
I'm guessing that you don't actually dive into each paper to 100% understand it? I find it takes me at least 10 hours of reading/looking things up per paper before I could consider that I fully understand it. But that would mean, if I want to do 4 papers per week, I'd spend at least 40 hours/week, that's like a full-time job, so obviously I don't have time for that.
How much time would you estimate it takes you to read through one paper? And how much of the content would you estimate gets retained and can be recalled when you wish?
I can read and fully understand an ML paper in an hour or so. But 6 months ago it took me a day to get through a couple of ML papers and I did not fully grok the mechanics of things like attention heads.
I'm more read in material science, chemistry, pharmacology, and cognitive science. Computer science (especially quantum computing, networking, and cryptography), photonics, and pure math are also big areas of interest for me.
Anything outside of that wheelhouse will take longer and I'll initially understand less, depending on how distant it is from my stronger subjects.
Other times I notice a general trend (ex. increasing discussion of a new paradigm X, more startups raising to work on Y, or a large chunk of talks at an annual conference being variations of Z).
Then I ask the forementioned academics and operators in my circle what papers I should read to get a handle on XYZ and/or simply follow the citations.
Given the amount of followers a lot of these researchers, operators, and science communicators have, I do not think I'm remotely unique in my efforts.
Depends on the paper's content but there's often sections that you don't need to 100% understand to get value. For example, in survey papers, there's typically a section that is basically "what queries we typed in at the library." I skip those and I think you can too =)
For practical papers, sometimes the evaluation can be skimmed. Author's benchmarks are usually designed to be the most favorable to the paper's novel approach, so I don't spend too much time thinking about them.
Similarly, Related Work sections can be skimmed. If you're well read in the field, you probably won't learn anything from it, and if you're entirely unread "its like X but different because Y" isn't helpful as you have no idea what X is, beyond the one dense sentence the paper just gave you.
> And how much of the content would you estimate gets retained and can be recalled when you wish?
If I really want to remember a paper, it goes into Anki flashcards. This is rare, personally. Usually only for tech I support in prod.
Do they? I suspect that most don't, and those that do are either in specialized careers or are engaged in some kind of scientific research.
Some interesting research gets disseminated via Twitter and chatrooms. Or maybe you follow a podcast that mentions new research. But you might also be following new publications from a handful of reputable journals, or following an Arxiv category, or looking through new conference papers. It's very easy to get overwhelmed with new research to read, and not knowing what's worth your time, unless you're already very familiar with the field and well-versed in the material.