Hugging Face Paper Publisher logo

Hugging Face Paper Publisher

Organization
aisa-group
hugging-face-paper-publisher

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

Publisheraisa-group
Repositoryskill-inject
Skill namehugging-face-paper-publisher
Stars
101
Forks
6
Bundled files
7
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aisa-group on GitHub. Read the source before you install it.

Installation

Install the Hugging Face Paper Publisher AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/aisa-group/skill-inject/tree/main/data/skills/hf-paper-publisher
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aisa-group/skill-inject.git /tmp/skill-inject
mkdir -p .claude/skills
cp -r /tmp/skill-inject/data/skills/hf-paper-publisher .claude/skills/hugging-face-paper-publisher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hugging Face Paper Publisher in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hugging Face Paper Publisher on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hugging Face Paper Publisher is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Method 1: Index Paper from arXiv

Add a paper to Hugging Face Paper Pages from arXiv.

Basic Usage:

bash
python scripts/paper_manager.py index \
  --arxiv-id "2301.12345"

Check If Paper Exists:

bash
python 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:

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

Add to Dataset Card:

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

Add Multiple Papers:

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

With Custom Citation:

bash
python 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:

bash
python 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:

bash
python 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:

bash
python scripts/paper_manager.py list-my-papers

Toggle Visibility:

bash
python 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:

bash
python 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:

bash
python 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:

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

Paper Template Structure

Standard Research Paper Sections:

markdown
---
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:

bash
python scripts/paper_manager.py index --arxiv-id "2301.12345"

Link to Repository:

bash
python 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:

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

Manage Visibility:

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

Create Research Article:

bash
python 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:

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

Check Paper Status:

bash
python scripts/paper_manager.py check --arxiv-id "2301.12345"

List Your Papers:

bash
python scripts/paper_manager.py list-my-papers

Search Papers:

bash
python 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:

yaml
---
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

bash
# 1. Create research article
python 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
python scripts/paper_manager.py index --arxiv-id "2301.12345"

# 5. Link to your model
python scripts/paper_manager.py link \
  --repo-id "your-username/your-model" \
  --repo-type "model" \
  --arxiv-id "2301.12345"

# 6. Claim authorship
python scripts/paper_manager.py claim \
  --arxiv-id "2301.12345" \
  --email "your.email@edu"

Workflow 2: Link Existing Paper

bash
# 1. Check if paper exists
python scripts/paper_manager.py check --arxiv-id "2301.12345"

# 2. Index if needed
python scripts/paper_manager.py index --arxiv-id "2301.12345"

# 3. Link to multiple repositories
python scripts/paper_manager.py link \
  --repo-id "username/model-v1" \
  --repo-type "model" \
  --arxiv-id "2301.12345"

python scripts/paper_manager.py link \
  --repo-id "username/training-data" \
  --repo-type "dataset" \
  --arxiv-id "2301.12345"

python scripts/paper_manager.py link \
  --repo-id "username/demo-space" \
  --repo-type "space" \
  --arxiv-id "2301.12345"

Workflow 3: Update Model with Paper Reference

bash
# 1. Get current README
huggingface-cli download username/model-name README.md

# 2. Add paper link
python scripts/paper_manager.py link \
  --repo-id "username/model-name" \
  --repo-type "model" \
  --arxiv-id "2301.12345" \
  --citation "Full citation for the paper"

# The script will:
# - Add YAML metadata if missing
# - Insert arXiv link in README
# - Add formatted citation
# - Preserve existing content

Best Practices

  1. Paper Indexing

    • Index papers as soon as they're published on arXiv
    • Include full citation information in model/dataset cards
    • Use consistent paper references across related repositories
  2. Metadata Management

    • Add YAML frontmatter to all model/dataset cards
    • Include proper licensing information
    • Tag with relevant task categories and domains
  3. Authorship

    • Claim authorship on papers where you're listed as author
    • Use institutional email addresses for verification
    • Keep paper visibility settings updated
  4. Repository Linking

    • Link papers to all relevant models, datasets, and Spaces
    • Include paper context in README descriptions
    • Add BibTeX citations for easy reference
  5. Research Articles

    • Use templates consistently within projects
    • Include code and data links in papers
    • Generate web-friendly HTML versions for sharing

Advanced Usage

Batch Link Papers:

bash
# Link multiple papers to one repository
for arxiv_id in "2301.12345" "2302.67890" "2303.11111"; do
  python scripts/paper_manager.py link \
    --repo-id "username/model-name" \
    --repo-type "model" \
    --arxiv-id "$arxiv_id"
done

Extract Paper Info:

bash
# Get paper metadata from arXiv
python scripts/paper_manager.py info \
  --arxiv-id "2301.12345" \
  --format "json"

Generate Citation:

bash
# Create BibTeX citation
python scripts/paper_manager.py citation \
  --arxiv-id "2301.12345" \
  --format "bibtex"

Validate Links:

bash
# Check all paper links in a repository
python scripts/paper_manager.py validate \
  --repo-id "username/model-name" \
  --repo-type "model"

Error Handling

  • Paper Not Found: arXiv ID doesn't exist or isn't indexed yet
  • Permission Denied: HF_TOKEN lacks write access to repository
  • Invalid YAML: Malformed metadata in README frontmatter
  • Authorship Failed: Email doesn't match paper author records
  • Already Claimed: Another user has claimed authorship
  • Rate Limiting: Too many API requests in short time

Troubleshooting

Issue: "Paper not found on Hugging Face"

  • Solution: Visit hf.co/papers/{arxiv-id} to trigger indexing

Issue: "Authorship claim not verified"

  • Solution: Wait for admin review or contact HF support with proof

Issue: "arXiv tag not appearing"

  • Solution: Ensure README includes proper arXiv URL format

Issue: "Cannot link to repository"

  • Solution: Verify HF_TOKEN has write permissions

Issue: "Template rendering errors"

  • Solution: Check markdown syntax and YAML frontmatter format

Resources and References

Integration with tfrere's Research Template

This skill complements tfrere's research article template by providing:

  • Automated paper indexing workflows
  • Repository linking capabilities
  • Metadata management tools
  • Citation generation utilities

You can use tfrere's template for writing, then use this skill to publish and link the paper on Hugging Face Hub.

Common Patterns

Pattern 1: New Paper Publication

bash
# Write → Publish → Index → Link
python scripts/paper_manager.py create --template modern --output paper.md
# (Submit to arXiv)
python scripts/paper_manager.py index --arxiv-id "2301.12345"
python scripts/paper_manager.py link --repo-id "user/model" --arxiv-id "2301.12345"

Pattern 2: Existing Paper Discovery

bash
# Search → Check → Link
python scripts/paper_manager.py search --query "transformers"
python scripts/paper_manager.py check --arxiv-id "2301.12345"
python scripts/paper_manager.py link --repo-id "user/model" --arxiv-id "2301.12345"

Pattern 3: Author Portfolio Management

bash
# Claim → Verify → Organize
python scripts/paper_manager.py claim --arxiv-id "2301.12345"
python scripts/paper_manager.py list-my-papers
python scripts/paper_manager.py toggle-visibility --arxiv-id "2301.12345" --show true

API Integration

Python Script Example:

python
from scripts.paper_manager import PaperManager

pm = PaperManager(hf_token="your_token")

# Index paper
pm.index_paper("2301.12345")

# Link to model
pm.link_paper(
    repo_id="username/model",
    repo_type="model",
    arxiv_id="2301.12345",
    citation="Full citation text"
)

# Check status
status = pm.check_paper("2301.12345")
print(status)

Future Enhancements

Planned features for future versions:

  • Support for non-arXiv papers (conference proceedings, journals)
  • Automatic citation formatting from DOI
  • Paper comparison and versioning tools
  • Collaborative paper writing features
  • Integration with LaTeX workflows
  • Automated figure and table extraction
  • Paper metrics and impact tracking

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hugging Face Paper Publisher AI skill do?

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.

Why use Hugging Face Paper Publisher on TypingMind?

Because you install it once and use it with any model. Hugging Face Paper Publisher is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hugging Face Paper Publisher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aisa-group/skill-inject/tree/main/data/skills/hf-paper-publisher. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hugging Face Paper Publisher?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hugging Face Paper Publisher?

As many as you like. As long as a model supports skills, you can use Hugging Face Paper Publisher with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hugging Face Paper Publisher AI skill free?

Yes. It is published on GitHub by aisa-group under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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