ml-paper-writing

To draft a publication-ready machine learning paper, you can generate a complete first version from your research repository by providing the code and prompting the AI to create a structured outline, full narrative sections, and a citation verification plan for major ML conferences.

Citation verification prevents hallucinated references by programmatically fetching BibTeX entries via Semantic Scholar, arXiv, and CrossRef APIs instead of generating them from memory, ensuring every cited work is real and accurately marked with placeholders if verification fails.

Yes, you can convert or resubmit drafts between NeurIPS, ICML, ICLR, ACL, AAAI, and COLM because the workflow applies conference-aware structural guidance to align abstracts, introductions, and limitations with specific venue requirements.

The best way to meet reviewer expectations is to structure your paper following the reviewer-focused hierarchy of title, abstract, introduction, and figures, while explicitly aligning claims, experiments, and limitations sections to standard evaluation criteria.

No, this academic writing workflow does not handle systems paper submissions; it explicitly routes systems venue submissions to a dedicated systems-paper-writing skill to ensure appropriate structural formatting.

Yes, you need to format limitations sections explicitly for top AI conferences like NeurIPS and ICML, as the drafting process enforces explicit limitations handling to comply with venue-specific submission requirements and reviewer checklists.