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Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain,...
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/ChonSong/skill-retriever --skill hugging-face-papers命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this,"...
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| name | hugging-face-papers |
| description | Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain,... |
| risk | unknown |
| source | https://github.com/huggingface/skills/tree/main/skills/huggingface-papers |
| source_repo | huggingface/skills |
| source_type | official |
| date_added | "2026-07-01T00:00:00.000Z" |
| license | Apache-2.0 |
| license_source | https://github.com/huggingface/skills/blob/main/LICENSE |
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:
| Input | Paper ID |
|---|---|
https://huggingface.co/papers/2602.08025 | 2602.08025 |
https://huggingface.co/papers/2602.08025.md | 2602.08025 |
https://arxiv.org/abs/2602.08025 |
2602.08025 |
https://arxiv.org/pdf/2602.08025 | 2602.08025 |
2602.08025v1 | 2602.08025v1 |
2602.08025 | 2602.08025 |
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:
curl -s "https://huggingface.co/papers/{PAPER_ID}.md"
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:
curl -s -H "Accept: text/markdown" "https://huggingface.co/papers/{PAPER_ID}"
All endpoints use the base URL https://huggingface.co.
Fetch the paper metadata as JSON using the Hugging Face REST API:
curl -s "https://huggingface.co/api/papers/{PAPER_ID}"
This returns structured metadata that can include:
To find models linked to the paper, use:
curl https://huggingface.co/api/models?filter=arxiv:{PAPER_ID}
To find datasets linked to the paper, use:
curl https://huggingface.co/api/datasets?filter=arxiv:{PAPER_ID}
To find spaces linked to the paper, use:
curl https://huggingface.co/api/spaces?filter=arxiv:{PAPER_ID}
Claim authorship of a paper for a Hugging Face user:
curl "https://huggingface.co/api/settings/papers/claim" \
--request POST \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $HF_TOKEN" \
--data '{
"paperId": "{PAPER_ID}",
"claimAuthorId": "{AUTHOR_ENTRY_ID}",
"targetUserId": "{USER_ID}"
}'
POST /api/settings/papers/claimpaperId (string, required): arXiv paper identifier being claimedclaimAuthorId (string): author entry on the paper being claimed, 24-char hex IDtargetUserId (string): HF user who should receive the claim, 24-char hex IDFetch the Daily Papers feed:
curl -s -H "Authorization: Bearer $HF_TOKEN" \
"https://huggingface.co/api/daily_papers?p=0&limit=20&date=2017-07-21&sort=publishedAt"
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:
curl -s -H "Authorization: Bearer $HF_TOKEN" \
"https://huggingface.co/api/papers?cursor={CURSOR}&limit=20"
GET /api/paperscursor (string): pagination cursorlimit (integer): number of results, between 1 and 100Perform hybrid semantic and full-text search on papers:
curl -s -H "Authorization: Bearer $HF_TOKEN" \
"https://huggingface.co/api/papers/search?q=vision+language&limit=20"
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 120Insert a paper from arXiv by ID. If the paper is already indexed, only its authors can re-index it:
curl "https://huggingface.co/api/papers/index" \
--request POST \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $HF_TOKEN" \
--data '{
"arxivId": "{ARXIV_ID}"
}'
POST /api/papers/indexarxivId (string, required): arXiv ID to index, for example 2301.00001^\d{4}\.\d{4,5}$Update the project page, GitHub repository, or submitting organization for a paper. The requester must be the paper author, the Daily Papers submitter, or a papers admin:
curl "https://huggingface.co/api/papers/{PAPER_OBJECT_ID}/links" \
--request POST \
--header "Content-Type: application/json" \
--header "Authorization: Bearer $HF_TOKEN" \
--data '{
"projectPage": "https://example.com",
"githubRepo": "https://github.com/org/repo",
"organizationId": "{ORGANIZATION_ID}"
}'
POST /api/papers/{paperId}/linkspaperId (string, required): Hugging Face paper object IDgithubRepo (string, nullable): GitHub repository URLorganizationId (string, nullable): organization ID, 24-char hex IDprojectPage (string, nullable): project page URLhttps://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}Authorization: Bearer $HF_TOKEN..md endpoint for reliable machine-readable output./api/papers/{PAPER_ID} when you need structured JSON fields instead of page markdown.