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Hugging Face Papers Skill · Data Ai

Hugging Face Papers – Read & Analyze AI Research Papers

Fetch and analyze Hugging Face paper pages or arXiv papers with markdown and metadata API.

Supports 14-day daily paper submissions, model/dataset linking, and GitHub integration. Download the skill now.

  • Hugging Face
  • arXiv
  • Research Papers
  • AI
  • Metadata
  • Markdown

About This Skill

This skill provides 2 primary ways to fetch paper content (markdown or structured metadata) from Hugging Face Paper pages and arXiv. It supports up to 14-day daily paper submissions, model/dataset/GitHub linking, and automatic indexing from model cards and READMEs.

Quick Start

  1. 1Install the skill from the marketplace.
  2. 2Provide a Hugging Face paper URL (e.g., https://huggingface.co/papers/2602.08025).
  3. 3Use the skill to fetch markdown content or structured metadata (authors, linked models, datasets, spaces, GitHub repo).
Example Command
fetch paper https://huggingface.co/papers/2602.08025 as markdown

Core Capabilities

Fetch Paper Markdown

Retrieve the full markdown content of any Hugging Face paper page or arXiv paper URL.

Fetch Structured Metadata

Get author names, linked models, datasets, Spaces, GitHub repo, and project page URLs as structured JSON.

Link Models, Datasets & Spaces

Automatically index papers mentioned in model cards, dataset cards, or Space READMEs, and link associated resources.

Daily Paper Submission & Voting

Submit papers to the Daily Papers feed within 14 days of arXiv publication, and upvote/comment on papers.

Usage Examples

Input

Fetch the markdown of paper https://huggingface.co/papers/2602.08025

Output

Returns the full paper content in markdown format including abstract, sections, and references.

Input

Get metadata for paper https://huggingface.co/papers/2602.08025

Output

Returns JSON with authors, linked models, datasets, Spaces, GitHub repo, and project page.

Before

Manually browsing hf.co/papers to check submission status.

After

Instant API response showing submission status and upvote count.

SKILL.md

---
source: "https://github.com/huggingface/skills/tree/main/skills/huggingface-papers"
name: hugging-face-papers
description: Read and analyze Hugging Face paper pages or arXiv papers with markdown and papers API metadata.
risk: unknown
---

# Hugging Face Paper Pages

Hugging Face Paper pages (hf.co/papers) is a platform built on top of arXiv (arxiv.org), specifically for research papers in the field of artificial intelligence (AI) and computer science. Hugging Face users can submit their paper at hf.co/papers/submit, which features it on the Daily Papers feed (hf.co/papers). Each day, users can upvote papers and comment on papers. Each paper page allows authors to:
- claim their paper (by clicking their name on the `authors` field). This makes the paper page appear on their Hugging Face profile.
- link the associated model checkpoints, datasets and Spaces by including the HF paper or arXiv URL in the model card, dataset card or README of the Space
- link the Github repository and/or project page URLs
- link the HF organization. This also makes the paper page appear on the Hugging Face organization page.

Whenever someone mentions a HF paper or arXiv abstract/PDF URL in a model card, dataset card or README of a Space repository, the paper will be automatically indexed. Note that not all papers indexed on Hugging Face are also submitted to daily papers. The latter is more a manner of promoting a research paper. Papers can only be submitted to daily papers up until 14 days after their publication date on arXiv.

The Hugging Face team has built an easy-to-use API to interact with paper pages. Content of the papers can be fetched as markdown, or structured metadata can be returned such as author names, linked models/datasets/spaces, linked Github repo and project page.

## When to Use
- User shares a Hugging Face paper page URL (e.g. `https://huggingface.co/papers/2602.08025`)
- User shares a Hugging Face markdown paper page URL (e.g. `https://huggingface.co/papers/26

Frequently Asked Questions

FAQ

Which paper URLs does this skill support?
It supports Hugging Face paper page URLs (e.g., https://huggingface.co/papers/2602.08025) and arXiv abstract/PDF URLs. It fetches content as markdown or structured metadata.
Who is this skill for?
This skill is designed for AI researchers, developers, and data scientists who need to quickly read and analyze research papers from Hugging Face and arXiv without leaving their workflow.
How is this different from directly visiting arXiv?
Unlike plain arXiv, Hugging Face Papers adds daily paper curation, upvoting, commenting, and automatic linking to models, datasets, and Spaces. This skill gives you programmatic access to all that enriched metadata.
What languages does the skill support?
The skill works with English-language papers (the primary language of arXiv and Hugging Face Papers). The API responses are in English.
What results can I expect from using this skill?
You can expect to receive the full paper markdown or structured metadata (authors, linked models/datasets/Spaces, GitHub repo, project page) within seconds. Papers submitted to daily papers within 14 days of arXiv publication are also accessible.

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Trigger Phrases

Use these phrases to activate this skill in your AI coding assistant:

fetch paperget paper metadataread hugging face paperanalyze arXiv paperpaper markdownpaper detailsdaily paperspaper submission status