Thank you for your interest in contributing! This document provides guidelines for contributing to this curated list.
- Fork the repository - Click the "Fork" button at the top right of the repository page
- Clone your fork -
git clone https://github.com/YOUR_USERNAME/graphrag-study.git - Create a branch -
git checkout -b add-new-resource - Make your changes - Add your resource following the guidelines below
- Commit your changes -
git commit -m "Add [resource name]" - Push to your fork -
git push origin add-new-resource - Submit a pull request - Open a PR from your fork to the main repository
- One resource per pull request - This makes it easier to review and discuss each addition
- Search before adding - Make sure your resource isn't already listed
- Check your spelling and grammar - Ensure descriptions are clear and professional
- Verify links - All URLs must be working and point to the correct resource
- Follow the format - Match the existing structure and style
- Keep descriptions concise - Aim for 1-2 sentences that clearly explain the resource's value
We welcome contributions in the following categories:
- Papers - Academic research, preprints, surveys (must include link to paper)
- Frameworks and Tools - Open source projects, libraries, platforms
- Tutorials and Courses - Educational content, guides, notebooks
- Videos and Talks - Conference presentations, tutorial videos, webinars
- Blog Posts - Technical articles, deep dives, case studies
- Datasets - Knowledge graphs, benchmarks, evaluation datasets
- Use Cases - Real-world applications and implementations
Resources should:
- Be directly related to GraphRAG or closely related technologies (knowledge graphs + RAG)
- Provide significant value to the community
- Be accessible (public links, not behind paywalls when possible)
- Be actively maintained (for tools and frameworks)
- Have clear documentation (for code/tools)
- **Paper Title** (Authors/Organization, Year)
- [Paper](URL) | Brief description of contribution
- Key findings or methodology- **[Tool Name](URL)** - Brief description
- Key feature 1
- Key feature 2
- Key feature 3- **Title** (Platform, Date if relevant)
- Brief description of content
- Target audience or prerequisites if relevantWithin each section, resources should be listed alphabetically. For papers, organize by subsection first, then alphabetically within each subsection.
- Use HTTPS links whenever possible
- For papers, prefer:
- Official publication page
- arXiv or other preprint server
- Author's website
- For code, link to the main repository (preferably GitHub)
- For articles, link to the original publication source
If you're unsure which section your resource belongs in:
- Papers - Peer-reviewed research, arXiv preprints, technical reports
- Frameworks and Tools - Code you can use to build GraphRAG systems
- Tutorials - Step-by-step guides and educational content
- Videos - Visual/audio content
- Blog Posts - Written articles and explainers (non-academic)
Please avoid:
- Promotional or marketing content without technical value
- Broken links or resources that are no longer available
- Duplicate content (check existing entries first)
- Resources behind strict paywalls (academic papers on publisher sites are OK)
- Personal projects without documentation or clear value
- Off-topic resources (pure LLM or pure graph content without RAG relevance)
If you believe a new section would benefit the list:
- Open an issue describing the proposed section
- Provide at least 3-5 resources that would fit in this section
- Explain why this deserves its own section
If you find:
- Broken links
- Incorrect information
- Misplaced resources
- Formatting issues
Please open an issue or submit a PR with the fix.
- Be respectful and professional
- Focus on the technical merit of resources
- Assume good faith in discussions
- Help maintain a welcoming environment for all contributors
If you have questions about contributing, please:
- Check existing issues and pull requests
- Review this guide thoroughly
- Open an issue with your question if still unclear
All contributors will be recognized in the project. Significant contributions may be highlighted in release notes.
Thank you for helping make this resource valuable for the GraphRAG community!