Beyond Market Intelligence/author guidelines

author guidelines

Beyond Market Intelligence keeps author guidelines in one place: 3 stories so far. The section currently leads with “Clarity in your ICLR rebuttal can help reviewers see your revisions”, “When AI reviews a paper, where do ICLR guidelines draw the line”, and “A Typo in ICLR's Template Has Persisted Since 2019”. Highlighting your ICLR rebuttal revisions in a different color is a smart, considerate move for busy reviewers. You're right to be cautious. 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 author guidelines story on Beyond Market Intelligence, newest first.

Machine Learning

Clarity in your ICLR rebuttal can help reviewers see your revisions

Highlighting your ICLR rebuttal revisions in a different color is a smart, considerate move for busy reviewers. It shows you respect their time and want to make your response as clear as possible. While the guidelines are silent, this practical approach is unlikely to cause issues. The key is to keep it subtle and functional, not decorative. For more on navigating conference feedback, our piece on "Navigating AI-Generated Peer Reviews at ICLR" offers further context on the review process.

Machine Learning

When AI reviews a paper, where do ICLR guidelines draw the line

You're right to be cautious. ICLR's guidelines require disclosure of AI use, which you're following, but they're silent on whether sharing the paper itself with an LLM is permitted. That silence creates real uncertainty. Many reviewers feel a second AI look could catch missed insights, but without explicit permission, the safest path is to avoid uploading the full paper. For deeper discussion on setting expectations, see our related piece, "A call to raise the bar on conference paper submissions."

Machine Learning

A Typo in ICLR's Template Has Persisted Since 2019

A typo in ICLR's official template has survived since 2019: the sample bibliography credits the Deep Learning book to "Goodfellow, Bengio, Courville, Bengio," complete with a nonexistent volume 1. Harmless, sure, but after last year's hallucinated reference desk rejections, it's a funny reminder that even peer review infrastructure has blind spots. More practically, the guidelines contradict themselves on page limits: submission says 9 pages, camera ready says 10. If you're revising after Nov 5, trust the template's 9.