Multi-Task Learning

Training a single model to solve multiple tasks simultaneously, sharing representations across tasks. In robot learning, multi-task models learn a common visual encoder and task-specific heads, or use task embeddings to condition a shared policy. Benefits include improved data efficiency (tasks share useful features) and deployment simplicity (one model serves many tasks).