Metaphorian: Leveraging Large Language Models to Support Extended Metaphor Creation for Science Writing
Open accessAbstract
Science writers commonly use extended metaphors to communicate unfamiliar concepts in a more accessible way to a wider audience. However, creating metaphors for science writing is challenging even for professional writers; according to our formative study (n=6), finding inspiration and extending metaphors with coherent structures were critical yet significantly challenging tasks for them. We contribute Metaphorian, a system that supports science writers with the creation of scientific metaphors by facilitating the search, extension, and iterative revision of metaphors. Metaphorian uses a large language model-based workflow inspired by the heuristic rules revealed from a study with six professional writers. A user study (n=16) revealed that Metaphorian significantly enhances satisfaction, confidence, and inspiration in metaphor writing without decreasing writers’ sense of agency. We discuss design implications for creativity support for figurative writing in science.
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Other domains including HCI, organization and business management, and cognitive science have explored the impact of LLMs on creativity.
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The Introduction and Section 4 describe an HCI study of an LLM-based tool for creative metaphor writing, so the paper supports HCI as an example. The passages do not address research in organization and business management or cognitive science, which are also attributed to the source in the citing sentence. No page numbers are available in our copy. (LLM, conf=0.84)
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Guo, P., Zhang, J., Shi, H., Xu, H., & Dong, Z. (2026) · Designing Interactive Systems Conference · doi:10.1145/3800645.3812967
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Co-Constructing Alignment: A Participatory Approach to Situating AI Values
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Attention to Innovation: Linking Developer Gaze and Coding Approaches
Lafhal, Y. A., Sharafi, Z., & Amini, M. (2026) · IEEE International Conference on Program Comprehension (ICPC) · doi:10.1145/3794763.3794790
- Authors
- Kim, J., Suh, S., Chilton, L. B., & Xia, H.
- Affiliations
- Stanford University (US)
- University of California San Diego (US)
- Columbia University (US)
- Venue
- Proceedings of the 2023 ACM Designing Interactive Systems Conference
- Publisher
- ACM
- Published
- 2023-07-10
- Pages
- 115-135
- OpenAlex
- W4383682897
- Cited by
- 61
- References
- 59
- Citations by year
- 2026: 13 · 2025: 29 · 2024: 18 · 2023: 1
- FWCI
- 53.92
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Designing Interactive Systems Conference (publishedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- extended metaphor, scientific writing, large language models, creativity support, figurative writing, heuristic rules, writer agency, science communication
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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