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…
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/2602.08025.md) User shares an arXiv URL (e.g. https://arxiv.org/abs/2602.08025 or https://arxiv.org/pdf/2602.08025) User mentions a arXiv ID (e.g. 2602.08025) User asks you to summarize, explain, or analyze an AI research paper
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