Summary
A discussion on r/ML clarifies that the 'lottery' perception of ML conference reviews primarily applies to papers that are good but not exceptional. Clearly strong or weak papers generally receive consistent outcomes, but the vast middle ground is where review variability becomes significant.
More context
The r/MachineLearning community engaged in a discussion regarding the common sentiment that ML conference reviews can feel like a "lottery." The prevailing view suggests this perception is nuanced, applying more to a specific category of submissions.
Additional details
- **Clear-cut cases:** Papers demonstrating genuinely solid contributions, strong execution, and clear understanding typically achieve acceptance. Conversely, papers that are clearly weak are usually filtered out.
- **The 'lottery' zone:** The variability and "weirdness" often complained about predominantly affect the large number of papers that are considered good but not undeniably outstanding. This "huge middle" is where the scale of submissions and inherent variability in the review process become significant factors.
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