ml-paper-writing

# ML Paper Writing for Top AI Conferences Expert-level guidance for writing publication-ready papers targeting **NeurIPS, ICML, ICLR, ACL, AAAI, and COLM**. This skill combines writing philosophy from top researchers (Nanda, Farquhar, Karpathy, Lipton, Steinhardt) with practical tools: LaTeX templates, citation verification APIs, and conference checklists. ## Default operating order Use this skill in the following order unless the task is unusually narrow: 1. lock the operating mode from `references/OPERATING-MODES.md`, 2. understand the repo or draft context, 3. use `references/citation-workflow.md` as the **canonical citation authority**, 4. load venue- or template-specific references only after the main writing path is clear. Google Scholar may still help with manual discovery, but it is **not** the canonical verification authority in this skill. Default verification should use programmatic sources such as Semantic Scholar, CrossRef, and arXiv. ## Core Philosophy: Collaborative Writing **Paper writing is collaborative, but Claude should be proactive in delivering drafts.** The typical workflow starts with a research repository containing code, results, and experimental artifacts. Claude's role is to: 1. **Understand the project** by exploring the repo, results, and existing documentation 2. **Deliver a complete first draft** when confident about the contribution 3. **Search literature** using web search and APIs to find relevant citations 4. **Refine through feedba...