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How to (seriously) read a scientific paper (2016)

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Re: How to (seriously) read a scientific paper (2016)

#3
post #2

Still waiting for an open discussion forum for scientific papers. Like StackOverflow, but every post is a paper. And there are experts of various gradations that help with questions.

I think researchgate tried to do that, but I don't know how successful they've been.

Re: How to (seriously) read a scientific paper (2016)

#4
This misses the best skimming trick I learned from an advisor: After you read the abstract, read the last couple lines/paragraphs of the introduction. That's where you'll find the authors best summary of the paper's contributions and novelty. For instance, the first paper that popped up with some random search terms [0]:

    The present paper attempts to provide a structured and comprehensive overview of state-of-the-art automated driving related hardware-software practices. [...] The aim of this paper is to fill this gap in the literature with a thorough survey.

    The remainder of this paper is written in eight sections. Section II is an overview [...] Details [...] are given in Section III. Section IV presents [...] etc.
When you have a meter high stack of papers for your lit review, comprehending long introductions and conclusions gets too expensive. You want to filter the irrelevant stuff as quickly as possible so you can spend time focused on the couple hundred papers you might actually read and cite.

[0] https://doi.org/10.1109/ACCESS.2020.2983149

Re: How to (seriously) read a scientific paper (2016)

#5
post #2

Still waiting for an open discussion forum for scientific papers. Like StackOverflow, but every post is a paper. And there are experts of various gradations that help with questions.

Individual subreddits have usually been my go-to place to discuss and understand the nuances of academic papers. Love LocalLLama for discussions on generative AI papers.

Re: How to (seriously) read a scientific paper (2016)

#10
I think it really depends on where in your career you are? Like if you are near the beginning:

* read the whole intro, make sure to look up any parts of the problem description you don’t understand

* at least skim the body of the work. If you are trying to implement a code, make sure to understand all the algorithm blocks and note how each one corresponds to the overall work so you don’t end up implementing a special case.

* read pay extra attention to the conclusion and skim the results

If you are experienced, I guess you don’t need advice, but I figure it is something like:

* skim the first couple sentences (for the problem) and the conclusion of the intro

* skip to the results section to see if the person is screwing you around with gamed metrics

* go back if it looks good and skim their ideas

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