ml-paper-writing

Topics in the source

• ML Paper Writing for Top AI Conferences
• Core Philosophy: Collaborative Writing
• ⚠️ CRITICAL: Never Hallucinate Citations
• The Problem
• The Rule
• When You Can't Verify a Citation
• Recommended: Install Exa MCP for Paper Search
• Workflow 0: Starting from a Research Repository

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. 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. -- This is the most important rule in academic writing wi

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