research-paper-writing

To write a machine learning research paper for conference submission, use this Skill to manage the end-to-end pipeline from literature review and experiment design to LaTeX formatting and venue-specific checklists for NeurIPS, ICML, or ICLR.

Structuring ML experiment design and statistical analysis involves planning execution monitoring, using scipy and numpy for data validation, and generating publication-ready figures with matplotlib and SciencePlots to support your paper's narrative.

Yes, the paper writing workflow supports citation verification by querying Semantic Scholar and arXiv through the habanero and requests dependencies to ensure references in your research papers are accurate and properly linked.

You can use LaTeX templates for AAAI, ACL, or COLM conference submissions because the Skill provides conference-specific guidance including formatting, limitations, ethics checklists, and alignment with reviewer expectations for each venue.

Iterative paper development handles reviewer response by supporting self-review, revision workflows, and drafting structured rebuttals that address reviewer expectations while maintaining experiment journals and research-grade validation.

Automating research paper writing for machine learning experiments is limited by the need for human evaluation guidance and requires scientists to provide preliminary experiment results to turn them into a coherent, submission-ready draft.