# Hugging Face Papers as a Gemini Notebook source

> A daily-curated feed of AI research, each paper with a discussion page that adds context.


_Markdown version of https://gemini-notebook-hub.online/sources/hugging-face-papers — for AI and LLM crawlers. Content is identical to the web page._

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- Site: [huggingface.co](https://huggingface.co/papers)
- Category: Code & ML research
- Access: free

A daily-curated feed of AI research, each paper with a discussion page that adds context.

A daily-curated feed of AI papers keeps a notebook current on what the field is discussing this week, which a keyword search on a slower index won't reliably surface. Discussion threads under each paper sometimes include the authors clarifying a method. Curation is small and driven by staff and community upvotes rather than systematic coverage, so it's a poor substitute for a real literature search.

## Import into Gemini Notebook

1. Copy the link: https://huggingface.co/papers
2. In your notebook, click Add source → Website.
3. Paste the link and confirm — several links can be pasted at once, one per line.

**Tip:** Documentation pages import better than repositories: paste a project's docs URL or README page, not the repo root.

## More code & ml research sources

- [Papers with Code](https://gemini-notebook-hub.online/sources/papers-with-code.md) — ML papers matched to their implementations and benchmarks — import the paper page and the README together.
- [GitHub](https://gemini-notebook-hub.online/sources/github.md) — READMEs, docs folders and wikis are strong sources for how a tool actually works — paste the rendered page URL.
- [MDN Web Docs](https://gemini-notebook-hub.online/sources/mdn-web-docs.md) — The reference for web platform APIs — reliable ground truth for a web-dev notebook.
- [Stack Exchange](https://gemini-notebook-hub.online/sources/stack-exchange.md) — Accepted answers on the technical sites make good targeted sources for narrow questions.