Vivian Liu


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Sparks: Inspiration for Science Writing using Language Models
Katy Gero | Vivian Liu | Lydia Chilton
Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)

Large-scale language models are rapidly improving, performing well on a variety of tasks with little to no customization. In this work we investigate how language models can support science writing, a challenging writing task that is both open-ended and highly constrained. We present a system for generating “sparks”, sentences related to a scientific concept intended to inspire writers. We run a user study with 13 STEM graduate students and find three main use cases of sparks—inspiration, translation, and perspective—each of which correlates with a unique interaction pattern. We also find that while participants were more likely to select higher quality sparks, the overall quality of sparks seen by a given participant did not correlate with their satisfaction with the tool.