Awesome-World-Models

Why we included this project

World-model research moves quickly enough that keeping up with the papers is a job in itself, and this index is built to make that job easier. It collects the foundational World Models paper, surveys, benchmarks, and recent technical reports, then groups them by application so you can tell general video-generation work apart from embodied-AI, VLA, visual-understanding, and autonomous-driving research. Each entry links to the paper, project website, and code where available, which saves real time when you want to reproduce or build on a specific approach. The maintainers accept pull requests and run an arXiv candidate pipeline to review new papers, so the list stays reasonably current. For researchers and engineers scoping work around predictive models, simulation, or robot learning, it is a useful map of who is doing what and where the code lives.