Collecting Interactive Multi-modal Datasets for Grounded Language Understanding
Human intelligence can remarkably adapt quickly to new tasks and
environments. Starting from a very young age, humans acquire new skills and
learn how to solve new tasks either by imitating the behavior of others or by
following provided natural language instructions. To facilitate research which
can enable similar capabilities in machines, we made the following
contributions (1) formalized the collaborative embodied agent using natural
language task; (2) developed a tool for extensive and scalable data collection;
and (3) collected the first dataset for interactive grounded language
understanding.