  Recent work in training large language models (LLMs) to follow natural
language instructions has opened up exciting opportunities for natural language
interface design. Building on the prior success of LLMs in the realm of
computer-assisted creativity, we aim to study if LLMs can improve the quality
of user-generated content through collaboration. We present CoPoet, a
collaborative poetry writing system. In contrast to auto-completing a user's
text, CoPoet is controlled by user instructions that specify the attributes of
the desired text, such as Write a sentence about `love' or Write a sentence
ending in `fly'. The core component of our system is a language model
fine-tuned on a diverse collection of instructions for poetry writing. Our
model is not only competitive with publicly available LLMs trained on
instructions (InstructGPT), but is also capable of satisfying unseen
compositional instructions. A study with 15 qualified crowdworkers shows that
users successfully write poems with CoPoet on diverse topics ranging from
Monarchy to Climate change. Further, the collaboratively written poems are
preferred by third-party evaluators over those written without the system.

Computation and Language