Congratulations to members of Changliu Liu’s Intelligent Control Lab Alvin Shek, Bo Ying Su and Rui Chen for winning the 2023 ICRA Outstanding Interaction Paper Award! For robots to be effectively deployed in novel environments and tasks, they must be able to understand the feedback expressed by humans during intervention. This can either correct undesirable behavior or indicate additional preferences. Existing methods either require repeated episodes of interactions or assume prior known reward features, which is data-inefficient and can hardly transfer to new tasks. We relax these assumptions by describing human tasks in terms of object-centric sub-tasks and interpreting physical interventions in relation to specific objects.