If the paper reinvents the wheel, they should indicate that clearly to the authors, pointing out which results are superseded. This AC just says "here's a bunch of papers you didn't cite, figure out whether this is new or not."
@thegautamkamath
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Unpunished Academic Misconduct: A Systemic Ethics Problem
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Yep. There's a lot of bad behaviours in academia that go unpunished. This is not good, but probably also one of the milder ones.
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Unlearnable Examples: False Security Against Future AI Systems
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Looks cool! However there's a critique that's been applied to unlearnable examples (
https://
arxiv.org/abs/2106.14851 ft @sanghyun_hong @florian_tramer
). Doesnt this give a false sense of security? Once released, future systems will be able to evade whatever defense is applied to the image -
Ethics of accusation: avoiding adversarial framing risks
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This one is at least feasible. But I'd still personally refrain from accusing anyone, since it's easy to frame someone adversarially or even accidentally.
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Security Vulnerability Identified as Potential Attack Vector
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Yeah, it does look pretty bad. But also seems like a nice attack vector 🙂
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Unethical AC Review Practices: Weaponizing Citations Against Researchers
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Unethical pro-tip: if you're an AC and you want to make someone else look bad, write a terrible meta-review and demand citations to many of their papers. Reminder that, despite the repeated authors here, we don't know who the ACs are. Don't jump to conclusions.
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Empathetic peer review in AI research publication process
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Usually, we think of AC rejections and being cold and uncaring. But this AC was quite empathetic, picking up on a self-critical comment from the author and supporting them in their journey. https://
openreview.net/forum?id=A6O79
ipjlJC
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Paper Rejection Despite Acceptance Scores Highlights Review Process Issues
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The paper was rejected despite all scores being "Accept" or better, because the AC says they didn't compare with some other papers, which were never mentioned before. The AC should have raised this to the authors earlier, or figured out the relevance with help of the reviewers.
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Tom Burns Shares Thoughtful Response to Peer Reviewers
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Tom (
@tfburns
) gives a thoughtful final response to his reviewers, which wasn't made public. Read it here! -
Detecting Non-Gaussian Distributions in Machine Learning Models
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The easiest way to see this is to fix the mean to be 0 and then observe that the returned value will never be negative. Thus it can't be Gaussian. Definitely not easy to spot.