ml-paper-writing

Draft ML/AI papers with narrative frameworks and citation verification workflows.

Updated Mar 16, 2026
One-click install
npx skills add https://github.com/arsity/scholar-tools --skill ml-paper-writing-arsity
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ml-paper-writing
Source: https://github.com/arsity/scholar-tools/tree/main/vendor/ai-research-skills/20-ml-paper-writing
Command: npx skills add https://github.com/arsity/scholar-tools --skill ml-paper-writing-arsity

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires semanticscholar, arxiv, habanero, requests, and includes references (resource) and assets (resource) components.

What problem does it solve?

Provides a comprehensive, field-ready framework that helps researchers draft publication-ready ML/AI papers from research repos, including narrative framing, structure templates, and citation workflows.

Core Features & Use Cases

  • Narrative framework: define What/Why/So What to anchor the paper’s contribution.
  • Abstract and structure guidance: 5-sentence abstract, introduction, methods, experiments, and related work templates.
  • Reproducibility & ethics: checklists for data, code, compute, limitations, and broader impacts.
  • Citation verification workflows: programmatic literature search, multi-source verification, and BibTeX retrieval with best-practice handling for placeholders.
  • LaTeX templates & submission guidelines: conference-specific formatting guidance and best practices for rigorous writing.

Quick Start

Draft your ML/AI paper by applying the narrative framework to outline the contribution, fill in the abstract and introduction, and validate citations using the verification workflow.

Quick Start

Draft your ML paper start-to-finish using the narrative framework and citation workflow.

Quick Start

Draft your ML paper by applying the narrative framework and citation workflow.

Quick Start

Draft your ML paper by applying the narrative framework and citation workflow.

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 publication-ready machine learning paper from a research repository?

To draft a publication-ready machine learning paper, you apply a What/Why/So What narrative framework to structure your abstract, introduction, methods, experiments, and related work directly from your research repository outputs.

What's the best way to verify citations and retrieve BibTeX entries for an ML conference submission?

For ML conference submission citation verification, you can run programmatic literature searches across arXiv and Semantic Scholar to validate references and automatically retrieve matching BibTeX entries.

Can I use this framework to generate reproducibility and ethics checklists for my ML paper?

Yes, you can generate reproducibility and ethics checklists for your ML paper, covering required documentation for compute resources, datasets, code availability, broader impacts, and limitations.

Does this paper writing workflow support specific LaTeX templates for different conference submissions?

Yes, the paper writing workflow provides conference-specific LaTeX templates and formatting guidelines to ensure your manuscript meets the strict submission requirements of targeted machine learning conferences.

How do I structure an effective abstract and introduction for an AI research paper?

To structure an effective AI research paper abstract and introduction, you follow a five-sentence abstract template and anchor your introduction around the What/Why/So What narrative contribution framework.

Do I need Semantic Scholar and arXiv access to verify references for my machine learning paper?

Yes, you need access to Semantic Scholar and arXink, as the automated citation verification and multi-source literature search workflows query these dependencies to validate your paper's references.