huggingface-paper-publisher

Publishing a machine learning research paper on the Hugging Face Hub involves automating arXiv indexing, verifying authorship, and linking models or datasets. This skill streamlines that workflow by generating structured markdown articles and metadata for reproducible research publishing.

Yes, you can generate BibTeX citations for arXiv papers and Hugging Face models. The skill provides citation generation utilities that automatically connect your research artifacts using proper metadata to ensure accurate referencing.

Linking an arXiv paper to a Hugging Face model repository requires applying proper metadata and citation tags. This skill automates research artifact linking, connecting your scientific articles directly with corresponding models and datasets on the Hub.

Yes, Hugging Face API integration is required to manage paper repositories and handle metadata. You need to configure your environment with API credentials using python-dotenv to authenticate and automate article generation and publishing workflows.

Available markdown templates include standard, modern, arXiv, and ML experiment report formats. The skill creates structured research articles by applying these templates during the scientific article generation process for publication-ready outputs.

Hugging Face paper publishing workflows can fail during authorship verification if metadata is incomplete or API credentials are missing. The skill automates authorship claims by validating metadata handling, requiring valid Hugging Face API integration to succeed.