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This version passed the hardening gate. Hardening applied 6 targeted changes and preserved all other text. Classified findings before hardening: 1. Classified findings closed: 1. Classified findings remaining: 0. Unclassified scanner findings remaining: 0. Review findings closed: 10. Review findings remaining: 7.
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Expand | File | Group | Subtype | Severity | Status |
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SKILL.md | Sensitive Data & Secret Exposure | Data exfiltration | Medium | Closed |
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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:
authors field). This makes the paper page appear on their Hugging Face profile.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.
https://huggingface.co/papers/2602.08025)https://huggingface.co/papers/2602.08025.md)https://arxiv.org/abs/2602.08025 or https://arxiv.org/pdf/2602.08025)2602.08025)It's recommended to parse the paper ID (arXiv ID) from whatever the user provides:
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This allows you to provide the paper ID into any of the hub API endpoints mentioned below.
The content of a paper can be fetched as markdown like so:
This should return the Hugging Face paper page as markdown. This relies on the HTML version of the paper at https://arxiv.org/html/{PAPER_ID}.
There are 2 exceptions:
Alternatively, you can request markdown from the normal paper page URL, like so:
All endpoints use the base URL https://huggingface.co.
Fetch the paper metadata as JSON using the Hugging Face REST API:
This returns structured metadata that can include:
To find models linked to the paper, use:
To find datasets linked to the paper, use:
To find spaces linked to the paper, use:
Fetch the Daily Papers feed:
GET /api/daily_papersp (integer): page numberlimit (integer): number of results, between 1 and 100date (string): RFC 3339 full-date, for example 2017-07-21week (string): ISO week, for example 2024-W03month (string): month value, for example 2024-01submitter (string): filter by submittersort (enum): publishedAt or trendingList arXiv papers sorted by published date:
GET /api/paperscursor (string): pagination cursorlimit (integer): number of results, between 1 and 100Perform hybrid semantic and full-text search on papers:
This searches over the paper title, authors, and content.
GET /api/papers/searchq (string): search query, max length 250limit (integer): number of results, between 1 and 120https://huggingface.co/papers/{PAPER_ID} or md endpoint: the paper is not indexed on Hugging Face paper pages yet./api/papers/{PAPER_ID}: the paper may not be indexed on Hugging Face paper pages yet.If the Hugging Face paper page does not contain enough detail for the user's question:
https://huggingface.co/papers/{PAPER_ID}https://arxiv.org/abs/{PAPER_ID}https://arxiv.org/pdf/{PAPER_ID}.md endpoint for reliable machine-readable output./api/papers/{PAPER_ID} when you need structured JSON fields instead of page markdown.Get started with chainctlchainctl skill install public/huggingface/huggingface-papers:latest
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HARDENING.md
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SKILL.md