Co-Pilot
Updated a month ago

hugging-face-paper-publisher

Hhuggingface
1.0k
huggingface/skills/skills/hugging-face-paper-publisher
82
Agent Score

💡 Summary

This skill facilitates the publication and management of research papers on the Hugging Face Hub, integrating with arXiv and enabling authorship verification.

🎯 Target Audience

AI researchersAcademic authorsData scientistsMachine learning practitionersStudents in AI/ML fields

🤖 AI Roast:Powerful, but the setup might scare off the impatient.

Security AnalysisMedium Risk

Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); API keys/tokens handling and storage; filesystem read/write scope and path traversal. Run with least privilege and audit before enabling in production.


name: hugging-face-paper-publisher description: Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.

Overview

This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers on the Hugging Face Hub. It streamlines the workflow from paper creation to publication, including integration with arXiv, model/dataset linking, and authorship management.

Integration with HF Ecosystem

  • Paper Pages: Index and discover papers on Hugging Face Hub
  • arXiv Integration: Automatic paper indexing from arXiv IDs
  • Model/Dataset Linking: Connect papers to relevant artifacts through metadata
  • Authorship Verification: Claim and verify paper authorship
  • Research Article Template: Generate professional, modern scientific papers

Version

1.0.0

Dependencies

  • huggingface_hub>=0.26.0
  • pyyaml>=6.0.3
  • requests>=2.32.5
  • markdown>=3.5.0
  • python-dotenv>=1.2.1

Core Capabilities

1. Paper Page Management

  • Index Papers: Add papers to Hugging Face from arXiv
  • Claim Authorship: Verify and claim authorship on published papers
  • Manage Visibility: Control which papers appear on your profile
  • Paper Discovery: Find and explore papers in the HF ecosystem

2. Link Papers to Artifacts

  • Model Cards: Add paper citations to model metadata
  • Dataset Cards: Link papers to datasets via README
  • Automatic Tagging: Hub auto-generates arxiv:<PAPER_ID> tags
  • Citation Management: Maintain proper attribution and references

3. Research Article Creation

  • Markdown Templates: Generate professional paper formatting
  • Modern Design: Clean, readable research article layouts
  • Dynamic TOC: Automatic table of contents generation
  • Section Structure: Standard scientific paper organization
  • LaTeX Math: Support for equations and technical notation

4. Metadata Management

  • YAML Frontmatter: Proper model/dataset card metadata
  • Citation Tracking: Maintain paper references across repositories
  • Version Control: Track paper updates and revisions
  • Multi-Paper Support: Link multiple papers to single artifacts

Usage Instructions

The skill includes Python scripts in scripts/ for paper publishing operations.

Prerequisites

  • Install dependencies: uv add huggingface_hub pyyaml requests markdown python-dotenv
  • Set HF_TOKEN environment variable with Write-access token
  • Activate virtual environment: source .venv/bin/activate

All paths are relative to the directory containing this SKILL.md file. Before running any script, first cd to that directory or use the full path.

Method 1: Index Paper from arXiv

Add a paper to Hugging Face Paper Pages from arXiv.

Basic Usage:

uv run scripts/paper_manager.py index \ --arxiv-id "2301.12345"

Check If Paper Exists:

uv run scripts/paper_manager.py check \ --arxiv-id "2301.12345"

Direct URL Access: You can also visit https://huggingface.co/papers/{arxiv-id} directly to index a paper.

Method 2: Link Paper to Model/Dataset

Add paper references to model or dataset README with proper YAML metadata.

Add to Model Card:

uv run scripts/paper_manager.py link \ --repo-id "username/model-name" \ --repo-type "model" \ --arxiv-id "2301.12345"

Add to Dataset Card:

uv run scripts/paper_manager.py link \ --repo-id "username/dataset-name" \ --repo-type "dataset" \ --arxiv-id "2301.12345"

Add Multiple Papers:

uv run scripts/paper_manager.py link \ --repo-id "username/model-name" \ --repo-type "model" \ --arxiv-ids "2301.12345,2302.67890,2303.11111"

With Custom Citation:

uv run scripts/paper_manager.py link \ --repo-id "username/model-name" \ --repo-type "model" \ --arxiv-id "2301.12345" \ --citation "$(cat citation.txt)"

How Linking Works

When you add an arXiv paper link to a model or dataset README:

  1. The Hub extracts the arXiv ID from the link
  2. A tag arxiv:<PAPER_ID> is automatically added to the repository
  3. Users can click the tag to view the Paper Page
  4. The Paper Page shows all models/datasets citing this paper
  5. Papers are discoverable through filters and search

Method 3: Claim Authorship

Verify your authorship on papers published on Hugging Face.

Start Claim Process:

uv run scripts/paper_manager.py claim \ --arxiv-id "2301.12345" \ --email "your.email@institution.edu"

Manual Process:

  1. Navigate to your paper's page: https://huggingface.co/papers/{arxiv-id}
  2. Find your name in the author list
  3. Click your name and select "Claim authorship"
  4. Wait for admin team verification

Check Authorship Status:

uv run scripts/paper_manager.py check-authorship \ --arxiv-id "2301.12345"

Method 4: Manage Paper Visibility

Control which verified papers appear on your public profile.

List Your Papers:

uv run scripts/paper_manager.py list-my-papers

Toggle Visibility:

uv run scripts/paper_manager.py toggle-visibility \ --arxiv-id "2301.12345" \ --show true

Manage in Settings: Navigate to your account settings → Papers section to toggle "Show on profile" for each paper.

Method 5: Create Research Article

Generate a professional markdown-based research paper using modern templates.

Create from Template:

uv run scripts/paper_manager.py create \ --template "standard" \ --title "Your Paper Title" \ --output "paper.md"

Available Templates:

  • standard - Traditional scientific paper structure
  • modern - Clean, web-friendly format inspired by Distill
  • arxiv - arXiv-style formatting
  • ml-report - Machine learning experiment report

Generate Complete Paper:

uv run scripts/paper_manager.py create \ --template "modern" \ --title "Fine-Tuning Large Language Models with LoRA" \ --authors "Jane Doe, John Smith" \ --abstract "$(cat abstract.txt)" \ --output "paper.md"

Convert to HTML:

uv run scripts/paper_manager.py convert \ --input "paper.md" \ --output "paper.html" \ --style "modern"

Paper Template Structure

Standard Research Paper Sections:

--- title: Your Paper Title authors: Jane Doe, John Smith affiliations: University X, Lab Y date: 2025-01-15 arxiv: 2301.12345 tags: [machine-learning, nlp, fine-tuning] --- # Abstract Brief summary of the paper... # 1. Introduction Background and motivation... # 2. Related Work Previous research and context... # 3. Methodology Approach and implementation... # 4. Experiments Setup, datasets, and procedures... # 5. Results Findings and analysis... # 6. Discussion Interpretation and implications... # 7. Conclusion Summary and future work... # References

Modern Template Features:

  • Dynamic table of contents
  • Responsive design for web viewing
  • Code syntax highlighting
  • Interactive figures and charts
  • Math equation rendering (LaTeX)
  • Citation management
  • Author affiliation linking

Commands Reference

Index Paper:

uv run scripts/paper_manager.py index --arxiv-id "2301.12345"

Link to Repository:

uv run scripts/paper_manager.py link \ --repo-id "username/repo-name" \ --repo-type "model|dataset|space" \ --arxiv-id "2301.12345" \ [--citation "Full citation text"] \ [--create-pr]

Claim Authorship:

uv run scripts/paper_manager.py claim \ --arxiv-id "2301.12345" \ --email "your.email@edu"

Manage Visibility:

uv run scripts/paper_manager.py toggle-visibility \ --arxiv-id "2301.12345" \ --show true|false

Create Research Article:

uv run scripts/paper_manager.py create \ --template "standard|modern|arxiv|ml-report" \ --title "Paper Title" \ [--authors "Author1, Author2"] \ [--abstract "Abstract text"] \ [--output "filename.md"]

Convert Markdown to HTML:

uv run scripts/paper_manager.py convert \ --input "paper.md" \ --output "paper.html" \ [--style "modern|classic"]

Check Paper Status:

uv run scripts/paper_manager.py check --arxiv-id "2301.12345"

List Your Papers:

uv run scripts/paper_manager.py list-my-papers

Search Papers:

uv run scripts/paper_manager.py search --query "transformer attention"

YAML Metadata Format

When linking papers to models or datasets, proper YAML frontmatter is required:

Model Card Example:

--- language: - en license: apache-2.0 tags: - text-generation - transformers - llm library_name: transformers --- # Model Name This model is based on the approach described in [Our Paper](https://arxiv.org/abs/2301.12345). ## Citation ```bibtex @article{doe2023paper, title={Your Paper Title}, author={Doe, Jane and Smith, John}, journal={arXiv preprint arXiv:2301.12345}, year={2023} }

**Dataset Card Example:**
```yaml
---
language:
  - en
license: cc-by-4.0
task_categories:
  - text-generation
  - question-answering
size_categories:
  - 10K<n<100K
---

# Dataset Name

Dataset introduced in [Our Paper](https://arxiv.org/abs/2301.12345).

For more details, see the [paper page](https://huggingface.co/papers/2301.12345).

The Hub automatically extracts arXiv IDs from these links and creates arxiv:2301.12345 tags.

Integration Examples

Workflow 1: Publish New Research

# 1. Create research article uv run scripts/paper_manager.py create \ --template "modern" \ --title "Novel Fine-Tuning Approach" \ --output "paper.md" # 2. Edit paper.md with your content # 3. Submit to arXiv (external process) # Upload to arxiv.org, get arXiv ID # 4. Index on Hugging Face uv run scripts/paper_manager.py index --arxiv-id "2301.12345" # 5. Link to your model uv r
5-Dim Analysis
Clarity8/10
Novelty7/10
Utility9/10
Completeness9/10
Maintainability8/10
Pros & Cons

Pros

  • Streamlines research paper publication
  • Integrates with arXiv for easy indexing
  • Supports authorship verification
  • Provides customizable templates for papers

Cons

  • Requires setup of environment variables
  • Dependency on external services like arXiv
  • May have a learning curve for new users
  • Limited to Hugging Face ecosystem

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Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.

Copyright belongs to the original author huggingface.