  Verbal communication plays a crucial role in human cooperation, particularly
when the partners only have incomplete information about the task, environment,
and each other's mental state. In this paper, we propose a novel cooperative
communication framework, Goal-Oriented Mental Alignment (GOMA). GOMA formulates
verbal communication as a planning problem that minimizes the misalignment
between the parts of agents' mental states that are relevant to the goals. This
approach enables an embodied assistant to reason about when and how to
proactively initialize communication with humans verbally using natural
language to help achieve better cooperation. We evaluate our approach against
strong baselines in two challenging environments, Overcooked (a multiplayer
game) and VirtualHome (a household simulator). Our experimental results
demonstrate that large language models struggle with generating meaningful
communication that is grounded in the social and physical context. In contrast,
our approach can successfully generate concise verbal communication for the
embodied assistant to effectively boost the performance of the cooperation as
well as human users' perception of the assistant.
