  Large language models (LLMs) can help writers build story worlds by
generating world elements, such as factions, characters, and locations.
However, making sense of many generated elements can be overwhelming. Moreover,
if the user wants to precisely control aspects of generated elements that are
difficult to specify verbally, prompting alone may be insufficient. We
introduce Patchview, a customizable LLM-powered system that visually aids
worldbuilding by allowing users to interact with story concepts and elements
through the physical metaphor of magnets and dust. Elements in Patchview are
visually dragged closer to concepts with high relevance, facilitating
sensemaking. The user can also steer the generation with verbally elusive
concepts by indicating the desired position of the element between concepts.
When the user disagrees with the LLM's visualization and generation, they can
correct those by repositioning the element. These corrections can be used to
align the LLM's future behaviors to the user's perception. With a user study,
we show that Patchview supports the sensemaking of world elements and steering
of element generation, facilitating exploration during the worldbuilding
process. Patchview provides insights on how customizable visual representation
can help sensemake, steer, and align generative AI model behaviors with the
user's intentions.
