hugging-face-paper-publisher

Indexing research papers from arXiv to Hugging Face involves using the huggingface_hub library to fetch arxiv metadata via requests and publish it directly to Hugging Face Paper Pages. This automates the initial creation and discoverability process for your academic work.

You can link your models, datasets, and spaces to relevant research papers on Hugging Face Hub. This repository linking connects your code artifacts directly to their underlying academic publications, ensuring proper attribution and significantly improving discoverability.

Generate markdown-based research articles for Hugging Face by utilizing built-in templates and the markdown library. This workflow creates professional research articles, streamlining the formatting and publication process directly within the Hugging Face ecosystem.

Claiming authorship on Hugging Face Paper Pages is best handled through a workflow automation skill that manages authorship directly via the huggingface_hub API. This ensures your user profile is properly linked to your published arXiv papers for accurate attribution.

You need python-dotenv to securely load environment variables, such as your Hugging Face API token, required by the huggingface_hub library. This dependency ensures safe authentication when automating your research paper publication and repository management workflows.

Pyyaml works with Hugging Face paper publishing workflows to manage and structure article templates and configuration metadata. It integrates alongside huggingface_hub and requests to automate the generation, linking, and indexing of your markdown-based research articles.