This is the most memorable abstract I've ever read.
Smith, Gordon C. S., and Jill P. Pell. 2003. “Parachute Use to Prevent Death and Major Trauma Related to Gravitational Challenge: Systematic Review of Randomised Controlled Trials.” BMJ 327 (7429): 1459–61. https://doi.org/10.1136/bmj.327.7429.1459.
Objectives: To determine whether parachutes are effective in preventing major trauma related to gravitational challenge.
Design: Systematic review of randomised controlled trials.
Data sources: Medline, Web of Science, Embase, and the Cochrane Library databases; appropriate internet sites and citation lists.
Study selection: Studies showing the effects of using a parachute during free fall.
Main outcome measure: Death or major trauma, defined as an injury severity score > 15.
Results: We were unable to identify any randomised controlled trials of parachute intervention.
Conclusions: As with many interventions intended to prevent ill health, the effectiveness of parachutes has not been subjected to rigorous evaluation by using randomised controlled trials. Advocates of evidence based medicine have criticised the adoption of interventions evaluated by using only observational data. We think that everyone might benefit if the most radical protagonists of evidence based medicine organised and participated in a double blind, randomised, placebo controlled, crossover trial of the parachute.
Contributors: GCSS had the original idea. JPP tried to talk him out of it. JPP did the first literature search but GCSS lost it. GCSS drafted the manuscript but JPP deleted all the best jokes. GCSS is the guarantor, and JPP says it serves him right.
I'm well into the thousands of research papers read. Understood a fair fraction of them. Couldn't tell you what the abstract was for any. The memorable parts are the ideas and the results within the paper.
Some titles stick. "Attention is all you need". "SSA is functional programming". Plus more people see the title than read the abstract. Only one I got to name myself was "Shared Memory Remote Procedure Calls" which I now realise is in exactly the same theme of given the title, you don't need the abstract or the contents.
An abstract and an introduction are two different things. For me, as a reader, the main role of the abstract is to help me to decide whether to even look at the rest of the paper, let alone read it. I want to know what is in the paper that I will not find in other papers that are competing for my time. Everything should be very clear: the context, the main research contributions and/or findings, novel aspects of the approach, limitations; plus any other information that in the author's view should motivate me to read the paper. Then if I do read the paper, there should not be any surprises: the content that the abstract promised should be present and, ideally, all of the valuable content in the paper should have been advertised in the abstract.
Different fields use different standard forms or styles for abstracts. If you have not already done so you can get a feel for this by looking at a random sample of the top 100 most-cited papers in your field (or your target conferences, journals, arxiv categories) and quickly compare to top 100 in a couple of disparate fields (e.g. biochemistry, economics, anthropology, mathematics).
Of course, there are good reasons to read a paper besides the quality and content of the abstract. Consequently, there are well known papers with non-standard abstracts. I recommend mastering the basics first.
Abstracts are not meant to be entertaining or memorable; they're meant to be highly functional. When you're reading a billion papers, a good abstract is important because it lets you get the gist of the paper and whether or not it's relevant to what you're researching in about 10 seconds. Make your abstract extremely clear and well structured about what you did, why, and your biggest finding, and the worry about giving it a good hook.
Hard to separate the memorability of the abstract from the underlying material.
IMO the most memorable papers contain some unexpected simplification: a complicated problem turns out to reduce to something much simpler [0], perhaps for a counterintuitive reason [1].
So a memorable abstract should advertise that the paper contains some cute little trick. This may not help you actually publish though
There's also the infamous opening paragraph to the "States of Matter" textbook by David L. Goodstein:
Ludwig Boltzmann, who spent much of his life studying statistical mechanics, died in 1906, by his own hand. Paul Ehrenfest, carrying on the work, died similarly in 1933. Now it is our turn to study statistical mechanics.
> I am a jackass who usually vibecodes my way through assignments but even I don't want to write a cookie-cutter intro for my paper. I wanna write something that stays with the reader
I don't have any examples to offer; but you may be missing your calling in Marketing
The ones with a memorable idea from the paper. People like to read about ideas that are interesting. If you can summarize an interesting idea and put it in the abstract, it will make it better.
I’m in the same boat that I don’t think the abstract itself of any I’ve read has been memorable in the slightest, but they usually serve to give me a tiny glimpse of whether or not I might find the underlying content interesting.
For example, I quite enjoyed the paper “Web Browser Fingerprinting Using Only Cascading Style Sheets,” but its abstract isn’t anything overly exciting. The title itself conveyed enough information for me to gather my interest, its attract just confirmed it was probably worth reading it.
The first thing to note is that papers vary wildly in terms of their information density and in terms of their accessibility and relevance to you as a reader. I can easily imagine reading some papers many times because I really want to understand all the details.
That said, the depth that I read at mostly depends on why I am reading something. Most papers I don't read in depth, but whether I initially only read the abstract or skim the whole paper depends a lot on a lot of factors (paper content, length, ease of access to full text, whether I am triaging a lot of papers at once, how interested I am in the specific paper (usually based on the title and/or authors, maybe the abstract), etc.).
I read in multiple passes of increasing depth. Zeroth reading is more-or-less triage: is the paper worth reading at all? First reading would generally be start-to-finish. I underline and/or mark up the margins with particularly interesting/important sections and also star key references based on the author's commentary.
If it's an algorithm or math-heavy paper either I only care about the gist and I don't go deeper, or I dig in with further readings and study to properly understand the details. That could be relatively quick, or it could be a whole rabbit hole if I need to learn some background. Sometimes it takes a while for the importance of a paper to dawn on me, in which case I come back later and read in more depth.
With the references I generally only follow those with relevance to my research goals. For example the authors might have detailed a technique in an earlier paper, or they might have cited other relevant work that I was not aware of.
Oh this is a super-important question, and I wish I'd gotten the following advice much earlier than I did:
1. First read the abstract and conclusion
2. Then flip through the figures and their captions, and try to understand them as best as you can (though this doesn't work for all papers)
3. Make a deliberate decision about whether it's worth it to dive into the details and read the full text.
LLMs are incredibly useful for parsing dense literature, but I think it's better to ask specific questions about the paper, jargon, equations etc. rather than to have it summarize the paper for you. Summaries are often shallow or even misleading, and they rob you of the opportunity to engage actively with the paper.
Memorability is, to me, strongly correlated with human effort. AI generally doesn't offer anything insightful, in my experience it doesnt produce useful insights as much as it summarises things.
So, if you want to be memorable, put in the effort snd have something to say that requires human expertise and the ability to generate non explicit insights.
This is the most memorable abstract I've ever read.
Smith, Gordon C. S., and Jill P. Pell. 2003. “Parachute Use to Prevent Death and Major Trauma Related to Gravitational Challenge: Systematic Review of Randomised Controlled Trials.” BMJ 327 (7429): 1459–61. https://doi.org/10.1136/bmj.327.7429.1459.
Objectives: To determine whether parachutes are effective in preventing major trauma related to gravitational challenge.
Design: Systematic review of randomised controlled trials.
Data sources: Medline, Web of Science, Embase, and the Cochrane Library databases; appropriate internet sites and citation lists.
Study selection: Studies showing the effects of using a parachute during free fall.
Main outcome measure: Death or major trauma, defined as an injury severity score > 15.
Results: We were unable to identify any randomised controlled trials of parachute intervention.
Conclusions: As with many interventions intended to prevent ill health, the effectiveness of parachutes has not been subjected to rigorous evaluation by using randomised controlled trials. Advocates of evidence based medicine have criticised the adoption of interventions evaluated by using only observational data. We think that everyone might benefit if the most radical protagonists of evidence based medicine organised and participated in a double blind, randomised, placebo controlled, crossover trial of the parachute.
Contributors: GCSS had the original idea. JPP tried to talk him out of it. JPP did the first literature search but GCSS lost it. GCSS drafted the manuscript but JPP deleted all the best jokes. GCSS is the guarantor, and JPP says it serves him right.
I'm well into the thousands of research papers read. Understood a fair fraction of them. Couldn't tell you what the abstract was for any. The memorable parts are the ideas and the results within the paper.
Some titles stick. "Attention is all you need". "SSA is functional programming". Plus more people see the title than read the abstract. Only one I got to name myself was "Shared Memory Remote Procedure Calls" which I now realise is in exactly the same theme of given the title, you don't need the abstract or the contents.
"SSA is functional programming" changed the course of my career. Memorable indeed.
Gotta have a look at yours! And I remember the name "Attention is all you need" too!
An abstract and an introduction are two different things. For me, as a reader, the main role of the abstract is to help me to decide whether to even look at the rest of the paper, let alone read it. I want to know what is in the paper that I will not find in other papers that are competing for my time. Everything should be very clear: the context, the main research contributions and/or findings, novel aspects of the approach, limitations; plus any other information that in the author's view should motivate me to read the paper. Then if I do read the paper, there should not be any surprises: the content that the abstract promised should be present and, ideally, all of the valuable content in the paper should have been advertised in the abstract.
Different fields use different standard forms or styles for abstracts. If you have not already done so you can get a feel for this by looking at a random sample of the top 100 most-cited papers in your field (or your target conferences, journals, arxiv categories) and quickly compare to top 100 in a couple of disparate fields (e.g. biochemistry, economics, anthropology, mathematics).
Of course, there are good reasons to read a paper besides the quality and content of the abstract. Consequently, there are well known papers with non-standard abstracts. I recommend mastering the basics first.
Oh, Thats interesting
Abstracts are not meant to be entertaining or memorable; they're meant to be highly functional. When you're reading a billion papers, a good abstract is important because it lets you get the gist of the paper and whether or not it's relevant to what you're researching in about 10 seconds. Make your abstract extremely clear and well structured about what you did, why, and your biggest finding, and the worry about giving it a good hook.
Hard to separate the memorability of the abstract from the underlying material.
IMO the most memorable papers contain some unexpected simplification: a complicated problem turns out to reduce to something much simpler [0], perhaps for a counterintuitive reason [1].
So a memorable abstract should advertise that the paper contains some cute little trick. This may not help you actually publish though
[0]: Attack the RLHF problem with a simple classification loss: https://arxiv.org/abs/2305.18290
[1]: Frustratingly Easy Meta-Embeddings: https://arxiv.org/abs/1804.05262
Not quite an abstract, but most memorable: https://onlinelibrary.wiley.com/doi/epdf/10.1111/meta.12599
There's also the infamous opening paragraph to the "States of Matter" textbook by David L. Goodstein:
Ludwig Boltzmann, who spent much of his life studying statistical mechanics, died in 1906, by his own hand. Paul Ehrenfest, carrying on the work, died similarly in 1933. Now it is our turn to study statistical mechanics.
Most memorable to me: https://www.ams.org/journals/bull/1966-72-06/S0002-9904-1966...
Short, succinct and no AI in sight.
Oooh, thanks!
see https://onlinelibrary.wiley.com/doi/pdf/10.1111/1467-968X.12...
include a SUMMARIUM in Latin and ΣΥΝΟΨΙΣ in Greek, for that real Scholar effect.
Haha, that oughta do the trick :D
> I am a jackass who usually vibecodes my way through assignments but even I don't want to write a cookie-cutter intro for my paper. I wanna write something that stays with the reader
I don't have any examples to offer; but you may be missing your calling in Marketing
https://lamport.azurewebsites.net/pubs/paxos-simple.pdf
"Abstract The Paxos algorithm, when presented in plain English, is very simple."
Appreciate it, thanks!
The ones with a memorable idea from the paper. People like to read about ideas that are interesting. If you can summarize an interesting idea and put it in the abstract, it will make it better.
I’m in the same boat that I don’t think the abstract itself of any I’ve read has been memorable in the slightest, but they usually serve to give me a tiny glimpse of whether or not I might find the underlying content interesting.
For example, I quite enjoyed the paper “Web Browser Fingerprinting Using Only Cascading Style Sheets,” but its abstract isn’t anything overly exciting. The title itself conveyed enough information for me to gather my interest, its attract just confirmed it was probably worth reading it.
I think it's the idea or my understanding of the paper that stays with me instead of the abstract
- big questions to you guys
- how do you actually go about reading one of these IEEE or arxiv papers?
- do you read only the abstract for most?
- do you read everything in 1 scan and what do you about references? do you follow through all the references?
- do you ask a GPT to help explain? what does your prompt look like?
The first thing to note is that papers vary wildly in terms of their information density and in terms of their accessibility and relevance to you as a reader. I can easily imagine reading some papers many times because I really want to understand all the details.
That said, the depth that I read at mostly depends on why I am reading something. Most papers I don't read in depth, but whether I initially only read the abstract or skim the whole paper depends a lot on a lot of factors (paper content, length, ease of access to full text, whether I am triaging a lot of papers at once, how interested I am in the specific paper (usually based on the title and/or authors, maybe the abstract), etc.).
I read in multiple passes of increasing depth. Zeroth reading is more-or-less triage: is the paper worth reading at all? First reading would generally be start-to-finish. I underline and/or mark up the margins with particularly interesting/important sections and also star key references based on the author's commentary.
If it's an algorithm or math-heavy paper either I only care about the gist and I don't go deeper, or I dig in with further readings and study to properly understand the details. That could be relatively quick, or it could be a whole rabbit hole if I need to learn some background. Sometimes it takes a while for the importance of a paper to dawn on me, in which case I come back later and read in more depth.
With the references I generally only follow those with relevance to my research goals. For example the authors might have detailed a technique in an earlier paper, or they might have cited other relevant work that I was not aware of.
Oh this is a super-important question, and I wish I'd gotten the following advice much earlier than I did:
1. First read the abstract and conclusion
2. Then flip through the figures and their captions, and try to understand them as best as you can (though this doesn't work for all papers)
3. Make a deliberate decision about whether it's worth it to dive into the details and read the full text.
LLMs are incredibly useful for parsing dense literature, but I think it's better to ask specific questions about the paper, jargon, equations etc. rather than to have it summarize the paper for you. Summaries are often shallow or even misleading, and they rob you of the opportunity to engage actively with the paper.
https://web.stanford.edu/class/cs114/reading-keshav.pdf is a way to do it. I just usually read it in one pass and then go back later and figure out the things I didn't understand.
"Theorems for free!" taught me that not all abstractions are leaky, and sometimes they're extra powerful.
Memorability is, to me, strongly correlated with human effort. AI generally doesn't offer anything insightful, in my experience it doesnt produce useful insights as much as it summarises things.
So, if you want to be memorable, put in the effort snd have something to say that requires human expertise and the ability to generate non explicit insights.
> I know I am a jackass who usually vibecodes my way through assignments but even I don't want to write a cookie-cutter intro for my paper.
+1 point for honesty.
-100 for being pathetically pathetic