Extensive experiments show that our method generates engaging manipulation results conforming to the transformations entailed in demonstrations.

In particular, most existing work only theoretically explains how the attention mechanism facilitates ICL under certain data models.

Safe reinforcement learning (RL) is a promising approach for many real-world decision-making problems where ensuring safety is a critical necessity.

Work done while visiting Harvard University.