BibTeX
3 stories filed under BibTeX on Beyond Market Intelligence. The newest of them: “A decade of ML research distilled into one clear page per topic”, “NeurIPS Acceptance Raises Questions About AI Review Justifications”, and “Explore how AI streamlines citation checks with transparent decision-making insights”. Ten years of machine learning research, 109,000 accepted papers, and one clear page per topic, that's what shipped today. An acceptance at NeurIPS should feel like a victory, but this one reads more like a puzzle. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every BibTeX story on Beyond Market Intelligence, newest first.
A decade of ML research distilled into one clear page per topic
Ten years of machine learning research, 109,000 accepted papers, and one clear page per topic, that's what shipped today. The team at Scime grouped every paper from ICML, NeurIPS, ICLR, CVPR, and AAAI since 2016 into about 1,260 topics, then pulled results tables and ablations from 79,000 of them. Take Gaussian splatting: 29 papers in 2023-24 ballooned to 240 in 2025-26, yet Deep Blending PSNR barely budged from 30.42 to 30.45. That's the kind of honest signal
NeurIPS Acceptance Raises Questions About AI Review Justifications
An acceptance at NeurIPS should feel like a victory, but this one reads more like a puzzle. The initial scores of 5/5/4 earned a positive meta-review, only for the final justification to flip negative, suggesting an AI-driven review process that doesn't add up. Even the flagged reference turned out to be a BibTeX copy-paste error. That's not rigor; it's noise. If the justification doesn't match the decision, we're not getting transparency, we're getting confusion.
Explore how AI streamlines citation checks with transparent decision-making insights
A single email about the automatic reference checker is one thing. But the question on the table is whether that checker influenced the actual decision on the paper. That is a meaningful distinction. Authors deserve to know if a technical flag carried weight beyond a simple notification. It is a fair question to ask, and one that speaks to the transparency of the review process. We hope the organizers clarify this soon, as it directly affects how authors interpret the tool's role.