Adaptive self-supervised learned model for controlling a vehicle

There is provided a the system configured to receive a pretrained model configured to output a plurality of representations based at least in part on an input comprising a graph representing an environment through which a vehicle is traversing, a node of the graph comprising, as an embedding, a vector encoding; receive a task comprising: a function to append to the pretrained model, a dataset, a loss function; and update, based at least in part on the task, the pretrained model to generate an updated machine learned model; and deploy the updated machine learned model to a vehicle computing system associated with a vehicle configured to be controlled based at least in part on an output of the updated machine learned model.