Completion Aware Guidance for World Action Models
World Action Models (WAMs) fail to complete tasks because their training objectives don't require finishing a task phase within each prediction step, leading to 'task-incomplete imagination.' Completion Aware Guidance (CAG) is a training-free sampling method that improves this by strengthening the conditioning of instruction tokens relevant to the current prediction. This guides the model toward necessary state transitions without retraining.