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.
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:
- Understand the project by exploring the repo, results, and existing documentation
- Deliver a complete first draft when confident about the contribution
- Search literature using web search and APIs to find relevant citations
- Refine through feedback cycles when the scientist provides input
- Ask for clarification only when genuinely uncertain about key decisions
Key Principle: Be proactive. If the repo and results are clear, deliver a full draft. Don't block waiting for feedback on every section—scientists are busy. Produce something concrete they can react to, then iterate based on their response.
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