Access and Summarize AI Research Papers
Fetches and manages Hugging Face Paper pages: markdown content, structured metadata, claims, and search.
Why it matters
Effortlessly retrieve and understand the latest AI research papers from Hugging Face and arXiv. This asset can fetch paper content, extract key metadata, and link to related models, datasets, and code repositories.
Outcomes
What it gets done
Parse paper IDs from various URL formats and mentions.
Fetch paper content as markdown or structured JSON metadata.
Identify and link associated models, datasets, and code repositories.
Summarize research paper abstracts and AI-generated summaries.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-hugging-face-papers | bash Overview
Hugging Face Paper Pages
Interacts with Hugging Face Paper pages: parsing paper IDs from any URL format, fetching content as markdown or structured metadata, and claiming, indexing, searching, or updating linked papers via the API. Use it when a user shares a Hugging Face or arXiv paper reference, or asks to summarize, explain, or analyze an AI research paper.
What it does
Interacts with Hugging Face Paper pages (hf.co/papers, built on arXiv for AI/CS research), where authors can claim their paper, link associated models, datasets, or Spaces, link a GitHub repo or project page, and link an organization - and where any HF paper or arXiv URL mentioned in a model, dataset, or Space README triggers automatic indexing, though only papers submitted within 14 days of their arXiv publication date can appear on the Daily Papers feed. It first parses a paper ID out of whatever the user provides - a Hugging Face papers URL, its .md variant, an arXiv abs or pdf URL, or a bare arXiv ID - then fetches content as markdown - either via the dedicated .md URL suffix or by sending an Accept: text/markdown header to the normal paper page URL, falling back to the arXiv HTML if no Hugging Face rendering exists - or as structured JSON metadata (authors, media, abstract and AI-generated summary, linked project or GitHub, organization, and upvote count).
curl -s "https://huggingface.co/papers/{PAPER_ID}.md"
Its full endpoint set covers finding models, datasets, or Spaces linked to a paper via an arxiv: filter, claiming authorship (POST /api/settings/papers/claim), fetching the Daily Papers feed with date, week, month, or submitter filters (GET /api/daily_papers), listing papers by cursor (GET /api/papers), hybrid semantic-plus-full-text search across title, authors, and content (GET /api/papers/search), indexing a new paper by arXiv ID (POST /api/papers/index - re-indexing an already-indexed paper is restricted to its authors), and updating a paper's project page, GitHub repo, or organization (POST /api/papers/{paperId}/links, restricted to the author, Daily Papers submitter, or a papers admin).
When to use - and when NOT to
Use it when a user shares a Hugging Face paper page URL, its markdown variant, an arXiv URL or bare arXiv ID, or asks to summarize, explain, or analyze an AI research paper.
Inputs and outputs
Input: a paper reference in any supported format, parsed down to a bare arXiv ID. Output: paper content as markdown or structured JSON - authors, summary, linked models, datasets, Spaces, GitHub or project links, and upvotes - or a write confirmation for claim, index, or link-update calls.
Integrations
Runs entirely against huggingface.co's REST API and paper-page markdown endpoints, falling back to arXiv's own abs or pdf pages when Hugging Face lacks sufficient detail. Read-only endpoints need no authentication; write endpoints - claim, index, update links - require Authorization: Bearer $HF_TOKEN.
Who it's for
Developers and agents that need to fetch, search, or manage Hugging Face paper-page content and metadata programmatically rather than browsing hf.co/papers by hand.
A 404 on either the paper page or its .md/API variant most often means the paper simply isn't indexed on Hugging Face yet, rather than a broken request - if a paper ID still can't be found, the next step is verifying the extracted arXiv ID itself, including any version suffix like v1.
FAQ
Common questions
Discussion
Questions & comments · 0
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