Verified:GitHub

ml-paper-writing

Draft machine learning papers from research repositories with verified citations.

Updated May 4, 2026

Search Tags:#machine learning #citation verification #paper writing #reviewer guidelines #research drafting #conference formatting

Ready to run

npx skills add https://github.com/Supporter09/Face_Anti_Spoofing_Biometric --skill ml-paper-writing-supporter09

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ml-paper-writing
Source: https://github.com/Supporter09/Face_Anti_Spoofing_Biometric/tree/main/.claude/skills/ml-paper-writing
Command: npx skills add https://github.com/Supporter09/Face_Anti_Spoofing_Biometric --skill ml-paper-writing-supporter09

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Helps researchers turn a machine learning project, codebase, and experimental notes into a clear, submission-ready paper without getting lost in structure, venue rules, or citation risk.

Core Features & Use Cases

Paper drafting: Builds a full ML/AI manuscript narrative around one strong contribution.
Venue adaptation: Adjusts structure and formatting for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM.
Citation safety: Verifies references programmatically and avoids hallucinated citations.
Research workflow support: Covers abstracts, introductions, methods, experiments, related work, limitations, and camera-ready or resubmission edits.
Use case: Use it when you have a research repository and want a first draft that is publication-oriented, reviewer-aware, and aligned with conference requirements.

Quick Start

Ask the assistant to analyze your research repository and produce a complete ML paper draft tailored to your target conference.

Frequently Asked Questions about ml-paper-writing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I draft a machine learning paper from my research repository?▼

To draft a machine learning paper from a research repository, the Skill analyzes your codebase and experimental notes to build a full publication-ready manuscript narrative around your core contribution. It structures the text to be reviewer-aware and aligned with conference formatting rules.

Can I format my ML paper draft for specific conferences like NeurIPS or ICML?▼

Yes, you can format your ML paper draft for specific conferences. The Skill provides venue adaptation for NeurIPS, ICML, ICLR, ACL, AAAI, and COLM by adjusting the manuscript structure and formatting to meet the exact requirements of your target venue.

How does citation verification work when writing an ML paper?▼

Citation verification works by programmatically checking references to prevent hallucinated citations during the paper writing process. The Skill ensures citation safety by requiring verified references, reducing the risk of including incorrect or fabricated literature in your manuscript.

What sections are included when generating a publication-ready ML paper?▼

Generating a publication-ready ML paper includes drafting abstracts, introductions, methods, experiments, related work, and limitations sections. The Skill also supports camera-ready edits, resubmission workflows, reproducibility details, and checklist compliance for a complete manuscript.

Do I need experimental notes and a codebase to start writing an AI research paper?▼

Yes, you need a research repository and experimental notes to start writing an AI research paper. The Skill requires these inputs to construct a coherent manuscript narrative, extract reproducibility details, and frame your methodology accurately for the target conference submission.

Are there limitations when adapting a research draft for conference formatting?▼

Limitations when adapting a research draft for conference formatting include the strict requirement for verified citations and reproducibility details. The Skill focuses on a single strong contribution and may not suit multi-focus manuscripts or repositories lacking clear experimental data.