releasing-research-code

Why we included this project

Releasing the code behind a paper is easy to get wrong, and this guide condenses what more than 200 popular machine learning repositories did right into a five-point checklist: dependencies, training code, evaluation code, pre-trained models, and a README with a results table plus the exact commands to reproduce it. Alongside the checklist you get a README template built from the sections well-received repos tend to include, and the data and notebooks used to back the analysis. Since NeurIPS later adopted the recommendations as official guidance, following them also lines you up with what reviewers at major ML venues expect. It is a reference and template set rather than software you run, which is exactly what you want open on screen while you write your own release.