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: 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 feedback cycles** when the scientist provides input 5. **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. --- ## ⚠️ CRITICAL: Never Hallucinate Citations **This is the most important rule in academic writing with AI assistance.** ### The Problem AI-generated citations have a **~40% error rate**. Hallucinated references—papers that don'...