A community-curated directory of notable computer science papers with local chapters for discussion and learning.
Papers We Love is a community-driven project that curates and organizes notable academic computer science papers into a searchable directory. It solves the problem of scattered research resources by providing a centralized collection and fosters learning through local chapter meetups and online discussions.
Computer science students, researchers, engineers, and enthusiasts who want to explore academic papers, stay updated with research trends, and participate in community discussions about technical literature.
Developers choose Papers We Love for its carefully curated paper selection, active global community with local meetups, and extensive supplementary resources including reading guides and alternative paper repositories.
Papers from the computer science community to read and discuss.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
The repository aggregates community-vetted computer science papers with quality indicators like scroll emojis for hosted content, as highlighted in the README's directory description.
Features local chapter meetups with a Code of Conduct and a Discord server for real-time discussions, fostering knowledge sharing beyond just paper links.
Includes an extensive wiki and README with links to other paper repositories, blogs, and reading guides, helping users find additional material easily.
Provides a command-line script (./scripts/download.sh) to scrape and download PDFs linked in the directory, simplifying access to papers with configurable options.
Due to licensing restrictions, many papers are not hosted directly, requiring users to follow external links that can be broken or inaccessible over time.
Relies on community pull requests for updates, which may lead to gaps in coverage, outdated links, or slower addition of new papers compared to automated systems.
As a markdown-based repository, it doesn't offer advanced search or filtering features, making it harder to navigate than dedicated paper databases with metadata support.