The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables.
We believe this is best done together with the community and powered by automation.
We hang out on Slack, come join us!
Anyone can contribute!
Want to submit a new code implementation? Search for the paper title, and then add the implementation on the paper page.
Want to add an evaluation table or a task? You'll see edit buttons on the paper and task pages - just go ahead and edit! We found this a fun way to learn about new areas of machine learning and staying in tune with research.
Please note that any contribution you make (i.e. linking code or submitting results) will be licensed under the free CC BY-SA licence.
To ensure high quality of data, all edits are monitored on Slack on the
#recentchanges channel. This is an open channel
and everyone is invited to follow and review contributions.
For a result to be included in a leaderboard we require that the paper is published as pre-print, in a conference or a journal. Having code is strongly encouraged but not required so we can capture the latest published results even before the code has been released.
All data is licenced under the CC BY-SA licence, same as Wikipedia.
The vast majority of the data is either annotated by the community or ourselves. However, we also included data from other resources that are published under a compatible licence, such as NLP-progress, EFF AI metrics, SQuAD and RedditSota.
More information on what has been included and how, please see the paperswithcode/sota-extractor repository.