ml-paper-writing

SkillDev tools

Helps your agent draft and polish ML research papers with LaTeX templates, citation checks, and conference guidelines.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the ml-paper-writing skill

About this capability

Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/33-Galaxy-Dawn-claude-scholar/skills/ml-paper-writing/SKILL.md and read by ahel’s review.

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 citationSearch API → verify → fetch BibTeXWrite BibTeX from memory
Uncertain about a paperMark as [CITATION NEEDED]Guess the reference
Can't find exact paperNote: "placeholder - verify"Invent similar-sounding paper

When You Can't Verify a Citation

If you cannot programmatically verify a citation, you MUST:

% EXPLICIT PLACEHOLDER - requires human verification

Signals

GitHub stars
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Last commit
Sep 2026
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Catalog kind
skill
Gateway key
ml-paper-writing
Source
github.com/brycewang-stanford/auto-empirical-research-skills