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ML conference paper length rules penalize theoretical work, researcher claims

A researcher on r/MachineLearning argues that current ML conference policies on paper length and self-containment unfairly penalize theoretical papers. The author suggests that reviewers often reject papers based on a lack of prerequisite knowledge or the perceived difficulty of terminology, rather than the impact of the work. This is exacerbated by rules that require papers to be self-contained and discourage reading appendices, leading to reviewer fatigue and arbitrary rejections. AI

IMPACT Could influence future discussions on academic publishing standards for AI research.

RANK_REASON The item is a personal opinion piece on a common issue in academic publishing, not a new release or significant event.

Read on r/MachineLearning →

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ML conference paper length rules penalize theoretical work, researcher claims

COVERAGE [1]

  1. r/MachineLearning TIER_1 English(EN) · /u/OutsideSimple4854 ·

    Paper lengths, and reasonable assumptions in ML conferences. [D]

    <!-- SC_OFF --><div class="md"><p>I've usually been commenting on threads on conference reviews. I'm now expressing my observations here.</p> <p>To the best of my knowledge, paper lengths have been held constant at many conferences, and some conferences have &quot;unlimited appen…