🏆 The 3DV Citations Grand Prix: the finale. P1, with 17,208 citations: “V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation” — Fausto Milletari, Nassir Navab & Seyed-Ahmad Ahmadi, 3DV 2016. arxiv.org/abs/1606.04797

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This makes me far more skeptical of theory-only papers. This doesn't just apply to academic writing. If you ask someone to invest the time in reading (an email, an ad, a blog post, or a million other things) - when it's clearly AI generated you're asking me to invest more time than you may have.

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Authors are asking reviewers to essentially play catch-the-error in AI generated theory papers. It feels like the time investment is incredibly imbalanced all of a sudden, reviewers may spend more time than authors, but the authors get the ultimate reward (a paper being accepted).

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One solution: normalize desk-rejections. After a fast first assessment, papers are either desk-rejected, or go to full review. The current conf peer-review system has desk rejects as the exception, as it relied on self-selection prior to submission and small numbers. Neither of these hold anymore.

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CVPR'27 (reg): 22 days. CVPR'27 (paper): 28 days. RSS'27 (ext-abs): 46 days. IJCAI'27 (reg): 77 days. IJCAI'27 (paper): 84 days. RSS'27 (paper): 179 days.

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