Comment on A.I. groks 66%-76% faster with data augmentation strategies.
Hackworth@lemmy.world 2 months agoWe follow the classic experimental paradigm reported in Power et al. (2022) for analyzing “grokking”, a poorly understood phenomenon in which validation accuracy dramatically improves long after the train loss saturates. Unlike the previous templates, this one is more amenable to open-ended empirical analysis (e.g. what conditions grokking occurs) rather than just trying to improve performance metrics
catloaf@lemm.ee 2 months ago
Oh okay so they’re just redefining words that are already well-defined so they can make fancy claims.
Hackworth@lemmy.world 2 months ago
Well-defined for casual use is very different than well-defined for scholarly research. It’s standard practice to take colloquial vocab and more narrowly define it for use within a scientific discipline. Sometimes different disciplines will narrowly define the same word two different ways, which makes interdisciplinary communication pretty funny.
technocrit@lemmy.dbzer0.com 2 months ago
No. It’s not standard at all, especially when the goal is overtly misleading.
Maybe one or both disciplines is promoting bullshit.
Hackworth@lemmy.world 2 months ago
Did you have a question?
Blueberrydreamer@lemmynsfw.com 2 months ago
Yeah slapping a wildly misleading literary reference that completely misuses the concept into a paper is not really standard practice. At least they gave it a different spelling so as to try to differentiate, it’s a shame that it wasn’t carried over to the title.