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            <namePart type="given">Ting-Hao</namePart>
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    <abstract>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.</abstract>
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%0 Conference Proceedings
%T Sparks: Inspiration for Science Writing using Language Models
%A Gero, Katy
%A Liu, Vivian
%A Chilton, Lydia
%Y Huang, Ting-Hao ’Kenneth’
%Y Raheja, Vipul
%Y Kang, Dongyeop
%Y Chung, John Joon Young
%Y Gissin, Daniel
%Y Lee, Mina
%Y Gero, Katy Ilonka
%S Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F gero-etal-2022-sparks
%X 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.
%R 10.18653/v1/2022.in2writing-1.12
%U https://aclanthology.org/2022.in2writing-1.12
%U https://doi.org/10.18653/v1/2022.in2writing-1.12
%P 83-84

Markdown (Informal)

[Sparks: Inspiration for Science Writing using Language Models](https://aclanthology.org/2022.in2writing-1.12) (Gero et al., In2Writing 2022)

• Sparks: Inspiration for Science Writing using Language Models (Gero et al., In2Writing 2022)

ACL

• Katy Gero, Vivian Liu, and Lydia Chilton. 2022. Sparks: Inspiration for Science Writing using Language Models. In Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022), pages 83–84, Dublin, Ireland. Association for Computational Linguistics.