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TLDR: Extreme Summarization of Scientific Documents

arxiv.org

11–20 of 41 posts

Re: TLDR: Extreme Summarization of Scientific Documents

#11
post #8

This kind of effort serves the function of helping people to _approximately_ "know what is known", but it's really not very useful to the more important part of research efforts, which is to know what is not known.

It could potentially be used with a novelty search algorithm, finding papers that are plausible but sufficiently dissimilar to anything in the training set.

Re: TLDR: Extreme Summarization of Scientific Documents

#14
post #8

This kind of effort serves the function of helping people to _approximately_ "know what is known", but it's really not very useful to the more important part of research efforts, which is to know what is not known.

A large part of research is spent on the understanding of what is known; parsing papers is part and parcel for professors, grad students, and corporate R+D alike.

No idea if their approach is useful, but they are tackling a worthwhile problem.

Re: TLDR: Extreme Summarization of Scientific Documents

#15
post #2

While there are lots of TLDR websites out there, I want to know how this one is different from them. I get it; many scientific papers are to some extent bs, and many are just wrong. For PhDs, it's a hassle to go through all of that bs to find something that is actually true. I feel like PhDs basically have to spend hundreds of hours reading papers that don't really benefit them. Tools like this could probably help wi…

It's Apache licensed and on github, which is substantially different from a lot of systems I see described in papers.

Re: TLDR: Extreme Summarization of Scientific Documents

#16

I played around with this on the demo page and found that while the generated "TLDR" are pretty good, they tend to generate sentences composed of fragments of existing sentences. Basically, it seems vaguely extractive in nature. Never did I see it summarize a concept in new words, or try to dumb down a complicated concept further than the original paper did. Given the results of GPT3 I would think that it should be p…

I think you’re underestimating how hard what you’re describing is. GPT-3 can mimic the language of reasoning but that doesn’t mean it’s capable of higher order reasoning.

Re: TLDR: Extreme Summarization of Scientific Documents

#17
post #8

This kind of effort serves the function of helping people to _approximately_ "know what is known", but it's really not very useful to the more important part of research efforts, which is to know what is not known.

A large part of research is spent on the understanding of what is known; parsing papers is part and parcel for professors, grad students, and corporate R+D alike. No idea if their approach is useful, but they are tackling a worthwhile problem.

> No idea if their approach is useful, but they are tackling a worthwhile problem.

When there are 1000+ papers every week in your field you need some advanced tools. It's hard to read everything, it's O(N).

Re: TLDR: Extreme Summarization of Scientific Documents

#18

Oh! I listened to Scott Hanselman interview one of the authors of this paper on his podcast the other day. It might interest some of you as she explains it all in a very accessible way: https://www.hanselminutes.com/763/tldr-extreme-summarization...

(hey peter!) I did get very excited about it when I heard about it, but cooled significantly when I learned that it was trained only on cs papers and required the full abstract plus paper text. nice proof of concept but going to need significant work to generalize for, say, a newsletter business like yours

Re: TLDR: Extreme Summarization of Scientific Documents

#19
post #2

While there are lots of TLDR websites out there, I want to know how this one is different from them. I get it; many scientific papers are to some extent bs, and many are just wrong. For PhDs, it's a hassle to go through all of that bs to find something that is actually true. I feel like PhDs basically have to spend hundreds of hours reading papers that don't really benefit them. Tools like this could probably help wi…

Never saw a paper lauded for its long length. Maybe the authors would have written shorter papers but they didn't have enough time.

Re: TLDR: Extreme Summarization of Scientific Documents

#20

That's what abstract are for

Abstracts are important (and clearly key in generating these TLDRs), but when it comes to ranking and recommending other papers (not to mention noting whether a new paper has content that can actually push a field forward) an abstract just isn't enough.
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