ml-paper-writing

To format a camera-ready ML paper, you need LaTeX templates specific to your target conference. This skill provides pre-configured LaTeX templates for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM to ensure correct formatting and submission readiness.

The best way to verify citations is using a programmatic workflow that fetches BibTeX entries and validates sources. This skill automates citation verification by querying Semantic Scholar, arXiv, and Crossref via the habanero library.

To structure arguments effectively, you can apply the What/Why/So What narrative framework. This skill provides narrative-writing guidance to help craft a clear, persuasive central contribution starting with your abstract and introduction.

Yes, you can draft publication-ready ML papers directly from code repositories. This skill structures arguments and formats manuscripts, transforming repository-level project details into reproducible, clearly argued academic texts.

Yes, the citation verification workflow supports fetching BibTeX entries from arXiv. It utilizes dependencies like semanticscholar, arxiv, and habanero to programmatically fetch and validate publication sources.

The What/Why/So What framework is a narrative-writing guidance tool used to craft a clear, persuasive central contribution. It helps structure arguments logically, ensuring your machine learning manuscript remains reproducible and clearly argued.