wtf is adajepa?

This is the official code release for a research paper called AdaJEPA, which is about how an AI system can plan actions in the real world, such as pushing an object to a target spot or navigating a maze. Systems like this often use a world model, a learned representation that predicts what the next state of the environment will look like after taking an action, and then plans a sequence of actions by imagining several possible futures. Normally that world model is trained once and then kept frozen while it is being used, so if conditions change from what it was trained on, its predictions get worse and planning can fail. AdaJEPA's contribution is to keep adjusting the world model while it is being used, instead of leaving it frozen. After planning and taking its first action, the system compares what it predicted would happen to what actually happened, uses that difference as a signal to update the model slightly, and then plans again with the improved model before taking the next action. This update loop repeats continuously as the task proceeds, without needing any extra human demonstrations, and the paper reports that this substantially improves planning success even with just one small update step between each replanning. The code builds on two earlier research projects, temporal-straightening and DINO-WM, and is meant for other researchers working in this area rather than for direct product use. It provides the training and adaptation code, configuration files for several types of environment shifts such as visual corruption, changed object shapes, changed physics, and unfamiliar maze layouts, and links to download pretrained checkpoints and evaluation data. Setup involves cloning the repository, creating the provided conda environment, and downloading separately hosted checkpoint and data files. Certain maze evaluations additionally require the MuJoCo physics simulator. The README includes example commands for running each type of evaluation and for visualizing what the model imagines compared to the real environment and the goal. The project includes a citation entry for the associated academic paper. No license file is described in the excerpt provided.