The DOI matches its Crossref record; 38 of the 39 references it cites were found in a registry or an index.
Metaphoria: An Algorithmic Companion for Metaphor Creation
Abstract
Creative writing, from poetry to journalism, is at the crux of human ingenuity and social interaction. Existing creative writing support tools produce entire passages or fully formed sentences, but these approaches fail to adapt to the writer's own ideas and intentions. Instead we posit to build tools that generate ideas coherent with the writer's context and encourage writers to produce divergent outcomes. To explore this, we focus on supporting metaphor creation. We present Metaphoria, an interactive system that generates metaphorical connections based on an input word from the writer. Our studies show that Metaphoria provides more coherent suggestions than existing systems, and supports the expression of writers' unique intentions. We discuss the complex issue of ownership in human-machine collaboration and how to build adaptive creativity support tools in other domains.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Early work on understanding AI co-writing in creative contexts suggested that AI involvement may decrease writers' sense of ownership [21, 22].”
From Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing Systems (2026) · cites this paper as [21]
In the citing paper
“Planning support in this context is focused on extending and organizing the user's ideas, often through analogies and cross-domain reasoning [38,62].”
From Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process (2025) · cites this paper as [38]
In the citing paper
“Our findings reinforce prior work that has also identified the importance of these three dimensions [31, 33, 71, 92].”
From Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation (2025) · cites this paper as [31]
In the citing paper
“One of the core abilities of GenAI is recognizing patterns from trained data and generating content [1], allowing for human-AI co-creative tasks and activities like writing [21,22,31], drawing [19,36], filmmaking [7,27,56,57] and more.”
From Child-AI Co-Creation: A Review of the Current Research Landscape and a Proposal for Six Design Considerations (2025) · cites this paper as [21]
Citations
Cites
Glove: Global Vectors for Word Representation
Pennington, J., Socher, R., & Manning, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1162 · Cited by 34,071
Advances in neural information processing systems 7
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90463-0 · Cited by 14,759
The way we think: conceptual blending and the mind's hidden complexities
(2002) · Choice Reviews Online · doi:10.5860/choice.40-1223 · Cited by 5,306
Norms of valence, arousal, and dominance for 13,915 English lemmas
Warriner, A. B., Kuperman, V., & Brysbaert, M. (2013) · Behavior Research Methods · doi:10.3758/s13428-012-0314-x · Cited by 1,959
From Word Embeddings To Document Distances
Kusner, M. J., Sun, Y., Kolkin, N., & Weinberger, K. Q. (2015) · PolyPublie (École Polytechnique de Montréal) · Cited by 1,695
ConceptNet — A Practical Commonsense Reasoning Tool-Kit
Liu, H., & Singh, P. (2004) · BT Technology Journal · doi:10.1023/b:bttj.0000047600.45421.6d · Cited by 1,570
Principles of mixed-initiative user interfaces
Horvitz, E. (1999) · Proceedings of the SIGCHI conference on Human factors in computing systems the CHI is the limit - CHI '99 · doi:10.1145/302979.303030 · Cited by 1,490
Dependency-Based Word Embeddings
Levy, O., & Goldberg, Y. (2014) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.3115/v1/p14-2050 · Cited by 1,125
Structure-mapping: A theoretical framework for analogy
GENTNER, D. (1983) · Cognitive Science · doi:10.1016/s0364-0213(83)80009-3 · Cited by 816
Soylent: a word processor with a crowd inside
Bernstein, M. S., Little, G., Miller, R. C., Hartmann, B., Ackerman, M. S., Karger, D. R., Crowell, D., & Panovich, K. (2010) · Proceedings of the 23nd annual ACM symposium on User interface software and technology · doi:10.1145/1866029.1866078 · Cited by 686
Research works printed but not linked: 10
- 10.5555/3505288.3505290 · DOI
- 10.1207/s15516709cog0702_3 · DOI · Paper page
- Sam Glucksberg, Matthew S McGlone, Yosef Grodzinsky, and Katrin Amunts. 2001. Understanding figurative language: From metaphor to idioms. Number 36. Oxford University Press on Demand.
- 10.7208/chicago/9780226470986.001.0001 · DOI
- 10.5555/1855062 · DOI
- 10.5555/2999792.2999959 · DOI
- Hugo Gonçalo Oliveira. 2012. PoeTryMe: a versatile platform for poetry generation. Computational Creativity, Concept Invention, and General Intelligence 1 (2012), 21.
- 10.5555/1619797.1619881 · DOI
- 10.5555/3019202 · DOI
- Ge Wang. 2008. The ChucK Audio Programming Language: An Stronglytimed and On-the-fly Environ/mentality. Ph.D. Dissertation. Princeton University.
Cited by
Sorted by citations
Design Guidelines for Prompt Engineering Text-to-Image Generative Models
Liu, V., & Chilton, L. B. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501825 · Cited by 639
Self-citationDesign Guidelines for Prompt Engineering Text-to-Image Generative Models
Liu, V., & Chilton, L. B. (2021) · arXiv · doi:10.48550/arxiv.2109.06977 · Cited by 635
Self-citationWu, T., Terry, M. A., & Cai, C. J. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517582 · Cited by 673
Wordcraft: Story Writing With Large Language Models
Yuan, A., Coenen, A., Reif, E., & Ippolito, D. (2022) · 27th International Conference on Intelligent User Interfaces · doi:10.1145/3490099.3511105 · Cited by 374
Lee, M., Liang, P., & Yang, Q. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502030 · Cited by 345
“The most traditional approach is contextual inquiry, inviting writers to write with an LM and interviewing them afterward [10, 14, 26, 63, 64, 66].”
BackgroundRezwana, J., & Maher, M. L. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3519026 · Cited by 342
Novice-AI Music Co-Creation via AI-Steering Tools for Deep Generative Models
Louie, R., Coenen, A., Huang, C. Z., Terry, M., & Cai, C. J. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376739 · Cited by 271
Co-Writing with Opinionated Language Models Affects Users’ Views
Jakesch, M., Bhat, A., Buschek, D., Zalmanson, L., & Naaman, M. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581196 · Cited by 265
“Studies have investigated interface design factors and interactions with writing assistants that directly or indirectly support inspiration [17, 70, 95, 105], language profciency [27], story writing [95, 105], text revision [36, 107] or creative writing [33, 46].”
BackgroundUsing artificial intelligence in craft education: crafting with text-to-image generative models
Vartiainen, H., & Tedre, M. (2023) · Digital Creativity · doi:10.1080/14626268.2023.2174557 · Cited by 263
TaleBrush: Sketching Stories with Generative Pretrained Language Models
Chung, J. J. Y., Kim, W., Yoo, K. M., Lee, H., Adar, E., & Chang, M. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501819 · Cited by 206
Large-scale Text-to-Image Generation Models for Visual Artists’ Creative Works
Ko, H.-K., Park, G., Jeon, H., Jo, J., Kim, J., & Seo, J. (2023) · Proceedings of the 28th International Conference on Intelligent User Interfaces · doi:10.1145/3581641.3584078 · Cited by 189
Homogenization Effects of Large Language Models on Human Creative Ideation
Anderson, B. R., Shah, J. H., & Kreminski, M. (2024) · Creativity and Cognition · doi:10.1145/3635636.3656204 · Cited by 188
Draxler, F., Werner, A., Lehmann, F., Hoppe, M., Schmidt, A., Buschek, D., & Welsch, R. (2024) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3637875 · Cited by 186
“…the user’s cursor in the text box or a “suggestion bar” above the key-board (cf. [3, 10, 15, 85]): For example, generated inspirational content is controlled and presented via sidebars [111], visual story arcs [21], manipulable metaphors [38], and modalities beyond text (e.g., images, sound) [96].”
BackgroundSparks: Inspiration for Science Writing using Language Models
Gero, K. I., Liu, V., & Chilton, L. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533533 · Cited by 161
Self-citationAI as Social Glue: Uncovering the Roles of Deep Generative AI during Social Music Composition
Suh, M. (., Youngblom, E., Terry, M., & Cai, C. J. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445219 · Cited by 138
A Design Space for Intelligent and Interactive Writing Assistants
Lee, M., Gero, K. I., Chung, J. J. Y., Shum, S. B., Raheja, V., Shen, H., Venugopalan, S., Wambsganss, T., Zhou, D., Alghamdi, E. A., et al. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642697 · Cited by 136
“An intelligent writing assistant within this context can provide support for diverse creative endeavors, including writing lyrics [257], crafting metaphors [84], and offering inspiration and assistance for storytelling [187, 220].”
InfluentialSelf-citationGenerative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking
Sharma, N., Liao, Q. V., & Xiao, Z. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642459 · Cited by 132
Social Dynamics of AI Support in Creative Writing
Gero, K. I., Long, T., & Chilton, L. B. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580782 · Cited by 129
Self-citationWhere to Hide a Stolen Elephant: Leaps in Creative Writing with Multimodal Machine Intelligence
Singh, N., Bernal, G., Savchenko, D., & Glassman, E. L. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3511599 · Cited by 119
Biermann, O. C., Ma, N. F., & Yoon, D. (2022) · Designing Interactive Systems Conference · doi:10.1145/3532106.3533506 · Cited by 116
Shaping Human-AI Collaboration: Varied Scaffolding Levels in Co-writing with Language Models
Dhillon, P. S., Molaei, S., Li, J., Golub, M., Zheng, S., & Robert, L. P. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642134 · Cited by 111
Lockton, D., Singh, D., Sabnis, S., Chou, M., Foley, S., & Pantoja, A. (2019) · Creativity and Cognition · doi:10.1145/3325480.3326570 · Cited by 111
Buschek, D., Zürn, M., & Eiband, M. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445372 · Cited by 108
Han, Y., Qiu, Z., Cheng, J., & Lc, R. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642133 · Cited by 146
Perfection Not Required? Human-AI Partnerships in Code Translation
Weisz, J. D., Muller, M., Houde, S., Richards, J., Ross, S. I., Martinez, F., Agarwal, M., & Talamadupula, K. (2021) · 26th International Conference on Intelligent User Interfaces · doi:10.1145/3397481.3450656 · Cited by 129
AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances
Agarwal, D., Naaman, M., & Vashistha, A. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713564 · Cited by 214
AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances
Agarwal, D., Naaman, M., & Vashistha, A. (2024) · arXiv · doi:10.48550/arxiv.2409.11360 · Cited by 99
AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models
Petridis, S., Diakopoulos, N., Crowston, K., Hansen, M., Henderson, K., Jastrzebski, S., Nickerson, J. V., & Chilton, L. B. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580907 · Cited by 98
Self-citationOpal: Multimodal Image Generation for News Illustration
Liu, V., Qiao, H., & Chilton, L. (2022) · Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3526113.3545621 · Cited by 104
Self-citationWan, Q., Hu, S., Zhang, Y., Wang, P., Wen, B., & Lu, Z. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637361 · Cited by 88
The Intersection of Users, Roles, Interactions, and Technologies in Creativity Support Tools
Chung, J. J. Y., He, S., & Adar, E. (2021) · Designing Interactive Systems Conference · doi:10.1145/3461778.3462050 · Cited by 102
Beyond Text Generation: Supporting Writers with Continuous Automatic Text Summaries
Dang, H., Benharrak, K., Lehmann, F., & Buschek, D. (2022) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3526113.3545672 · Cited by 103
Peng, Z., Guo, Q., Tsang, K. W., & Ma, X. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376695 · Cited by 81
Kim, T., Shin, D., Kim, Y.-H., & Hong, H. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642693 · Cited by 75
Osone, H., Lu, J.-L., & Ochiai, Y. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411763.3450391 · Cited by 74
LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexia
Goodman, S. M., Buehler, E., Clary, P., Coenen, A., Donsbach, A., Horne, T. N., Lahav, M., MacDonald, R., Michaels, R. B., Narayanan, A., et al. (2022) · Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3517428.3544819 · Cited by 71
Better Together? An Evaluation of AI-Supported Code Translation
Weisz, J. D., Muller, M., Ross, S. I., Martinez, F., Houde, S., Agarwal, M., Talamadupula, K., & Richards, J. T. (2022) · 27th International Conference on Intelligent User Interfaces · doi:10.1145/3490099.3511157 · Cited by 69
The Idea Machine: LLM-based Expansion, Rewriting, Combination, and Suggestion of Ideas
Fede, G. D., Rocchesso, D., Dow, S. P., & Andolina, S. (2022) · Creativity and Cognition · doi:10.1145/3527927.3535197 · Cited by 68
PopBlends: Strategies for Conceptual Blending with Large Language Models
Wang, S., Petridis, S., Kwon, T., Ma, X., & Chilton, L. B. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580948 · Cited by 64
Self-citationBridging the Gap Between UX Practitioners’ Work Practices and AI-Enabled Design Support Tools
Lu, Y., Zhang, C., Zhang, I., & Li, T. J.-J. (2022) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3491101.3519809 · Cited by 86
Kim, J., Suh, S., Chilton, L. B., & Xia, H. (2023) · Proceedings of the 2023 ACM Designing Interactive Systems Conference · doi:10.1145/3563657.3595996 · Cited by 61
Self-citationChakrabarty, T., Padmakumar, V., Brahman, F., & Muresan, S. (2024) · Creativity and Cognition · doi:10.1145/3635636.3656201 · Cited by 61
User Perspectives on Ethical Challenges in Human-AI Co-Creativity: A Design Fiction Study
Rezwana, J., & Maher, M. L. (2023) · Creativity and Cognition · doi:10.1145/3591196.3593364 · Cited by 60
Kim, T. S., Lee, Y., Chang, M., & Kim, J. (2023) · Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3586183.3606833 · Cited by 56
ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-Creation
Fan, X., Wu, Z., Yu, C., Rao, F., Shi, W., & Tu, T. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642129 · Cited by 51
Modeling Motivational Interviewing Strategies on an Online Peer-to-Peer Counseling Platform
Shah, R. S., Holt, F. V., Hayati, S. A., Agarwal, A., Wang, Y.-C., Kraut, R. E., & Yang, D. (2022) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3555640 · Cited by 67
Hoque, M. N., Mashiat, T., Ghai, B., Shelton, C. D., Chevalier, F., Kraus, K., & Elmqvist, N. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641895 · Cited by 48
Generating similes effortlessly like a Pro: A Style Transfer Approach for Simile Generation
Chakrabarty, T., Muresan, S., & Peng, N. (2020) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.524 · Cited by 55
Woo, D. J., Wang, Y., Susanto, H., & Guo, K. (2023) · Journal of Educational Computing Research · doi:10.1177/07356331231175999 · Cited by 44
MERMAID: Metaphor Generation with Symbolism and Discriminative Decoding
Chakrabarty, T., Zhang, X., Muresan, S., & Peng, N. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.336 · Cited by 67
Metaphors in Voice User Interfaces: A Slippery Fish
Desai, S., & Twidale, M. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3609326 · Cited by 42
Zhou, Z., Li, J., Zhang, Z., Yu, J., & Duh, H. B. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2370635 · Cited by 47
CreaTable Content and Tangible Interaction in Aphasia
Neate, T., Roper, A., Wilson, S., Marshall, J., & Cruice, M. N. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376490 · Cited by 43
Schmitt, O., & Buschek, D. (2021) · Creativity and Cognition · doi:10.1145/3450741.3465253 · Cited by 41
Jin, Y., Yoon, J., Self, J. A., & Lee, K. (2024) · Archives of Design Research · doi:10.15187/adr.2024.07.37.3.25 · Cited by 48
Enhancing Data Literacy On-Demand: LLMs as Guides for Novices in Chart Interpretation
Choe, K., Lee, C., Lee, S., Song, J., Cho, A., Kim, N. W., & Seo, J. (2024) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3413195 · Cited by 41
From Pen to Prompt: How Creative Writers Integrate AI into their Writing Practice
Guo, A., Sathyanarayanan, S., Wang, L., Heer, J., & Zhang, A. X. (2025) · Creativity and Cognition · doi:10.1145/3698061.3726910 · Cited by 61
Co-Writing with AI, on Human Terms: Aligning Research with User Demands Across the Writing Process
Reza, M., Thomas-Mitchell, J., Dushniku, P., Laundry, N., Williams, J. J., & Kuzminykh, A. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757566 · Cited by 37
“This indicates an area where users might benefit from proffering granular control over AI involvement.”
MetaWriter: Exploring the Potential and Perils of AI Writing Support in Scientific Peer Review
Sun, L., Tao, S., Hu, J., & Dow, S. P. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637371 · Cited by 37
Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation
He, J., Houde, S., & Weisz, J. D. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713522 · Cited by 36
Ding, Z., Srinivasan, A., Macneil, S., & Chan, J. (2023) · Creativity and Cognition · doi:10.1145/3591196.3593516 · Cited by 35
Wan, Q., Feng, X., Bei, Y., Gao, Z., & Lu, Z. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642410 · Cited by 39
How Novelists Use Generative Language Models: An Exploratory User Study.
Calderwood, A., Qiu, V., Gero, K. I., & Chilton, L. B. (2020) · Cited by 35
Self-citationAshkinaze, J., Mendelsohn, J., Qiwei, L., Budak, C., & Gilbert, E. (2025) · Proceedings of the ACM Collective Intelligence Conference · doi:10.1145/3715928.3737481 · Cited by 33
Louie, R., Engel, J., & Huang, C.-Z. A. (2022) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3490099.3511159 · Cited by 46
AI Writing Assistants Influence Topic Choice in Self-Presentation
Poddar, R., Sinha, R., Naaman, M., & Jakesch, M. (2023) · Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544549.3585893 · Cited by 30
Yeo, S., Lim, G., Gao, J., Zhang, W., & Perrault, S. T. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642530 · Cited by 43
What Makes Tweetorials Tick: How Experts Communicate Complex Topics on Twitter
Gero, K. I., Liu, V., Huang, S. X. L., Lee, J., & Chilton, L. B. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3479566 · Cited by 30
Self-citationHuman-AI Collaboration in Cooperative Games: A Study of Playing Codenames with an LLM Assistant
Sidji, M., Smith, W., & Rogerson, M. J. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3677081 · Cited by 39
A Design Space for Writing Support Tools Using a Cognitive Process Model of Writing
Gero, K., Calderwood, A., Li, C., & Chilton, L. (2022) · Proceedings of the First Workshop on Intelligent and Interactive Writing Assistants (In2Writing 2022) · doi:10.18653/v1/2022.in2writing-1.2 · Cited by 25
Self-citationReviewFlow: Intelligent Scaffolding to Support Academic Peer Reviewing
Sun, L., Chan, A., Chang, Y. S., & Dow, S. P. (2024) · ACM International Conference on Intelligent User Interfaces (IUI) · doi:10.1145/3640543.3645159 · Cited by 35
Ai.llude: Investigating Rewriting AI-Generated Text to Support Creative Expression
Zhou, D., & Sterman, S. (2024) · Creativity and Cognition · doi:10.1145/3635636.3656187 · Cited by 35
Yin, M., Han, B., Ryu, S., & Hua, M. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-48057-7_18 · Cited by 33
AI-Assisted Causal Pathway Diagram for Human-Centered Design
Zhong, R., Shin, D.-H., Meza, R. D., Klasnja, P., Colusso, L. F., & Hsieh, G. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642179 · Cited by 28
Lai, H., & Nissim, M. (2024) · ACM Computing Surveys · doi:10.1145/3654795 · Cited by 32
Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations
Kim, Y., Lee, S.-J., & Donahue, C. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713818 · Cited by 23
“Journey of Finding the Best Query”: Understanding the User Experience of AI Image Generation System
Kim, S., Eun, J., Oh, C., & Lee, J. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2307670 · Cited by 29
Mapping the Design Space of Human-AI Interaction in Text Summarization
Cheng, R., Smith-Renner, A., Zhang, K., Tetreault, J., & Jaimes-Larrarte, A. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2022.naacl-main.33 · Cited by 20
Qin, P., Yang, C.-L., Li, J., Wen, J., & Lee, Y. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713146 · Cited by 43
Writing with AI Lowers Psychological Ownership, but Longer Prompts Can Help
Joshi, N., & Vogel, D. (2025) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3719160.3736608 · Cited by 47
Interpretable Directed Diversity: Leveraging Model Explanations for Iterative Crowd Ideation
Wang, Y., Venkatesh, P., & Lim, B. Y. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517551 · Cited by 21
Authors' Values and Attitudes Towards AI-bridged Scalable Personalization of Creative Language Arts
Kim, T., Han, H., Adar, E., Kay, M., & Chung, J. J. Y. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642529 · Cited by 20
When to Give Feedback: Exploring Tradeoffs in the Timing of Design Feedback
E, J. L., Yen, Y.-C. G., Pan, I. Y., Lin, G. H. C., Li, M., Jin, H., Chen, M., Xia, H., & Dow, S. P. (2024) · Creativity and Cognition · doi:10.1145/3635636.3656183 · Cited by 25
Poetry Machines: Eliciting Designs for Interactive Writing Tools from Poets
Booten, K., & Gero, K. I. (2021) · Creativity and Cognition · doi:10.1145/3450741.3466813 · Cited by 21
Self-citationCai, Z., Han, A., Zhou, X., Gazulla, E. D., & Peppler, K. (2025) · Proceedings of the 24th Interaction Design and Children · doi:10.1145/3713043.3731506 · Cited by 17
Examining Agency, Expertise, and Roles of AI Systems in AI-Mediated Communication
Mieczkowski, H., & Hancock, J. (2022) · doi:10.31219/osf.io/asnv4 · Cited by 16
A hybrid human–AI tool for scientometric analysis
Correia, A., Grover, A., Jameel, S., Schneider, D., Antunes, P. A., & Fonseca, B. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10548-7 · Cited by 18
The Dearth of the Author in AI-Supported Writing
Kreminski, M. (2024) · Workshop on Intelligent and Interactive Writing Assistants (In2Writing) · doi:10.1145/3690712.3690725 · Cited by 13
An Exploration of Mental Models of AI in Human–AI Co-Creativity: A Framework and Insights
Rezwana, J., & Maher, M. L. (2025) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3769072 · Cited by 15
Probing Simile Knowledge from Pre-trained Language Models
Chen, W., Chang, Y., Zhang, R., Pu, J., Chen, G., Zhang, L., Xi, Y., Chen, Y., & Su, C. (2022) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.18653/v1/2022.acl-long.404 · Cited by 13
The use of ChatGPT in creative writing assistance
Фіялка, С. Б., Kornieva, Z., & Гончарук, Т. Г. (2024) · XLinguae · doi:10.18355/xl.2024.17.01.01 · Cited by 23
Evaluating Creativity Support Tools via Homogenization Analysis
Anderson, B. R., Shah, J. H., & Kreminski, M. (2024) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3613905.3651088 · Cited by 11
ChatGPT: A reliable assistant for the evaluation of students’ written texts?
Atasoy, A., & Arani, S. M. N. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13553-1 · Cited by 19
Phraselette: A Poet’s Procedural Palette
Calderwood, A., Chung, J. J. Y., Sun, Y., Roemmele, M., & Kreminski, M. (2025) · Designing Interactive Systems Conference · doi:10.1145/3715336.3735832 · Cited by 11
LaMPost: AI Writing Assistance for Adults with Dyslexia Using Large Language Models
Goodman, S. M., Buehler, E., Clary, P., Coenen, A., Donsbach, A., Horne, T. N., Lahav, M., MacDonald, R., Michaels, R. B., Narayanan, A., et al. (2024) · Communications of the ACM · doi:10.1145/3626952 · Cited by 16
A Human-Computer Collaborative Editing Tool for Conceptual Diagrams
Pan, L., Yu, C., He, Z., & Shi, Y. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580676 · Cited by 12
Roemmele, M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.04007 · Cited by 24
Kariyawasam, H., Niwarthana, A., Palmer, A., Kay, J., & Withana, A. (2024) · Proceedings of the 29th International Conference on Intelligent User Interfaces · doi:10.1145/3640543.3645161 · Cited by 9
CoCo Matrix: Taxonomy of Cognitive Contributions in Co-writing with Intelligent Agents
Wan, R., Gebreegziabher, S. A., Li, T. J.-J., & Badillo-Urquiola, K. (2024) · Creativity and Cognition · doi:10.1145/3635636.3664260 · Cited by 9
Karolus, J., Feger, S. S., Schmidt, A., & Woźniak, P. W. (2023) · Designing Interactive Systems Conference · doi:10.1145/3563657.3596052 · Cited by 9
Metadata
- Authors
- Gero, K. I., & Chilton, L. B.
- Affiliations
- Columbia University (US)
- Venue
- Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2019-05-02
- Pages
- 1-12
- OpenAlex
- W2941884113
- Cited by
- 146
- References
- 39
- Citations by year
- 2026: 15 · 2025: 24 · 2024: 39 · 2023: 21 · 2022: 23 · 2021: 17 · 2020: 6 · 2019: 1
- FWCI
- 171.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Funders
- National Science Foundation (DGE - 1644869)
- Topics
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Artistic and Creative Research
- Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- metaphor production, human-machine collaboration
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 ›
Are you an author, or do you see a problem with this page? Request a review