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DeepGamingAI t1_iusdqfr wrote

Think of it as a GAN, you train generators when you publish and train your discriminator when you review. Do these processes together alternately and you can see what you'll slowly converge to :)

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curiousshortguy t1_iutwnuz wrote

I think this is a terrible analogy. Reviewing isn't about rejecting. It's about enabling good scholarship and guiding researchers.

Putting the review as the gatekeeper just gives you shitty results, as seen by the last round of reviews at large conferences with uneducated and unqualified reviewers.

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DeepGamingAI t1_iuv83lt wrote

>It's about enabling good scholarship and guiding researchers.

You just described the role of a discriminator in a gan

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>uneducated and unqualified reviewers

op got an invite because they published there before, its on merit not a random review request. besides, the question solely focuses on how reviewing benefits the reviewer, it doesnt seem to cover the whole picture surrounding peer review system

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curiousshortguy t1_iuvswa7 wrote

>You just described the role of a discriminator in a gan

I disagree. The discriminator is just used in a binary fashion and doesn't add a lot of explanatory value.

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Just to clarify, I am not trying to say that OP is unqualified. But I think just thinking about it in a binary way isn't enough for good peer review and a functioning system.

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rustyryan t1_ivx9why wrote

The critic provides gradients to the generator, which indicate what aspects of its generation led to the classification.

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dssevero t1_iuyj0q1 wrote

Horrible analogy. While the discriminator improves the generator, there are no resulting consequences for the real/fake samples. This is completely different.

Besides, you can do this without the obligation of reviewing (which I encourage you to do).

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