--- name: ml-paper-writing description: Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows. version: 1.1.0 author: Orchestra Research license: MIT tags: [Academic Writing, NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP, LaTeX, Paper Writing, Citations, Research, Systems] dependencies: [semanticscholar, arxiv, habanero, requests] --- # ML Paper Writing for Top AI & Systems Conferences Expert-level guidance for writing publication-ready papers targeting **NeurIPS, ICML, ICLR, ACL, AAAI, COLM** (ML/AI venues) and **OSDI, NSDI, ASPLOS, SOSP** (Systems venues). 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't exist, wrong authors, incorrect years, fabricated DOIs—are a serious form of academic misconduct that can result in desk rejection or retraction. ### The Rule **NEVER generate BibTeX entries from memory. ALWAYS fetch programmatically.** | Action | ✅ Correct | ❌ Wrong | |--------|-----------|----------| | Adding a citation | Search API → verify → fetch BibTeX | Write BibTeX from memory | | Uncertain about a paper | Mark as `[CITATION NEEDED]` | Guess the reference | | Can't find exact paper | Note: "placeholder - verify" | Invent similar-sounding paper | ### When You Can't Verify a Citation If you cannot programmatically verify a citation, you MUST: ```latex % EXPLICIT PLACEHOLDER - requires human verification