ml-paper-writing

To write a publication-ready Machine Learning paper, this Skill drafts paper sections based on your research repository, structures arguments, and verifies citations programmatically. It supports top AI conferences like NeurIPS, ICML, and ICLR.

Preventing citation hallucination in ML papers is handled by programmatically fetching and verifying citations through Semantic Scholar, arXiv, and habanero. This ensures all references in academic writing are validated against actual sources.

Yes, you can use LaTeX templates for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM conference formatting. The Skill provides structured guidance and templates to prepare camera-ready submissions for these top-tier AI venues.

Yes, this Skill supports drafting academic papers directly from a GitHub repository. It can outline the introduction, methods, and related work sections based on the provided research repository and scientist feedback.

The best way to structure an introduction and related work for an ICML paper is using the Skill's structured guidance. It helps structure arguments, draft sections from your research repository, and ensures adherence to academic writing principles.

Yes, you need Semantic Scholar, arXiv, and habanero dependencies to verify citations for ML papers. These dependencies enable programmatic fetching and verification, preventing citation hallucination during academic writing.