ML conference paper limits may disadvantage theory research

The post stems from the author's experience as a theoretical machine learning researcher publishing at major venues. They note that major conferences including NeurIPS, ICML, and AAAI have maintained constant paper lengths over time, typically with the option to include unlimited appendices. Originally, these limits reflected the economics of printing proceedings; in the modern era, they serve an additional purpose: preventing reviewer fatigue by capping the volume of text any single reviewer must evaluate.

However, the author questions whether this one-size-fits-all approach fairly serves all research types. Theoretical papers, the author's focus, necessarily require readers to absorb prerequisite knowledge—at minimum, linear algebra and discrete mathematics—before engaging with the paper's novel contribution. Beyond these fundamentals, subfield-specific knowledge becomes essential. This graduated complexity of background material is inherent to theory work and cannot be easily compressed without sacrificing rigor or clarity.

The author's central frustration is that rejected theoretical papers, in their experience, rarely fail because the theory itself is weak. Rather, rejection seems to stem from factors they characterize as arbitrary. This pattern suggests that the fixed page constraint may be the operative obstacle: reviewers may struggle to fairly evaluate theory papers when the format does not adequately accommodate the requisite exposition, making the paper appear weaker than it is in fact.

This observation addresses a structural mismatch in how academic conferences apply uniform constraints to diverse research types. Paper-length limits were originally a practical necessity—printing costs drove the need to cap proceedings size—but persist today partly as a mechanism to manage reviewer effort. The researcher's concern is not that limits exist, but that they apply equally to theoretical and empirical work despite different knowledge prerequisites.

Theoretical papers require readers to absorb foundational concepts (linear algebra, discrete mathematics, subfield background) before engaging with the novel contribution. Empirical papers, by contrast, can often present results more directly. When page limits force both types into the same container, theoretical work faces a compounding burden: not only must it convey its results, but it must do so while assuming less shared understanding among reviewers. The researcher's observation that rejected theory papers often fail for "arbitrary reasons" rather than weak theory itself hints that the constraint—not the science—may be the barrier.

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