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CreativeConnect: Supporting Reference Recombination for Graphic Design Ideation with Generative AI

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Choi, DaEun, Hong, Sumin, Park, Jeongeon, Chung, John Joon Young, Kim, Juho·2024·Proceedings of the CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3613904.3642794
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Abstract

Graphic designers often get inspiration through the recombination of references. Our formative study (N=6) reveals that graphic designers focus on conceptual keywords during this process, and want support for discovering the keywords, expanding them, and exploring diverse recombination options of them, while still having room for designers’ creativity. We propose CreativeConnect, a system with generative AI pipelines that helps users discover useful elements from the reference image using keywords, recommends relevant keywords, generates diverse recombination options with user-selected keywords, and shows recombinations as sketches with text descriptions. Our user study (N=16) showed that CreativeConnect helped users discover keywords from the reference and generate multiple ideas based on them, ultimately helping users produce more design ideas with higher self-reported creativity, compared to the baseline system without generative pipelines. While CreativeConnect was shown effective in ideation, we discussed how CreativeConnect can be extended to support other types of tasks in creativity support.

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  1. [1][1] Steven Bird, Ewan Klein, and Edward Loper. 2009. Natural language processing with Python: analyzing text with the natural language toolkit . " O'Reilly Media, Inc.". -
  2. [2][2] Margaret A. Boden. 1998. Creativity and artificial intelligence. Artificial Intelligence 103, 1 (1998), 347-356. https://doi.org/10.1016/S0004-3702(98)00055-1 - · DOI · Paper page
  3. [3][3] Nathalie Bonnardel. 1999. Creativity in design activities: The role of analogies in a constrained cognitive environment. In Proceedings of the 3rd conference on Creativity & cognition . 158-165. -
  4. [4][4] Nathalie Bonnardel and Evelyne Marmèche. 2005. Towards supporting evocation processes in creative design: A cognitive approach. International Journal of Human-Computer Studies 63, 4 (2005), 422-435. https://doi.org/10.1016/j.ijhcs. 2005.04.006 Computer support for creativity. - · DOI
  5. [5][5] Stephen Brade, Bryan Wang, Mauricio Sousa, Sageev Oore, and Tovi Grossman. 2023. Promptify: Text-to-Image Generation through Interactive Prompt Exploration with Large Language Models. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (San Francisco, CA, USA) (UIST '23) . Association for Computing Machinery, New York, NY, USA, Article 96, 14 pages. https://doi.org/10.1145/3586183.3606725 - · DOI
  6. [6][6] Tim Brooks, Aleksander Holynski, and Alexei A. Efros. 2023. InstructPix2Pix: Learning to Follow Image Editing Instructions. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 18392-18402. -
  7. [7][7] Donald T Campbell. 1960. Blind variation and selective retentions in creative thought as in other knowledge processes. Psychological review 67, 6 (1960), 380. -
  8. [8][8] Tracy Cassidy. 2011. The Mood Board Process Modeled and Understood as a Qualitative Design Research Tool. Fashion Practice 3, 2 (2011), 225-251. https://doi.org/10.2752/175693811X13080607764854 arXiv:https://doi.org/10.2752/175693811X13080607764854 - · DOI
  9. [9][9] Joel Chan, Steven Dang, and Steven P. Dow. 2016. Comparing Different Sensemaking Approaches for Large-Scale Ideation. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '16) . Association for Computing Machinery, New York, NY, USA, 2717-2728. https://doi.org/10.1145/2858036.2858178 - · DOI
  10. [10][10] Minghao Chen, Iro Laina, and Andrea Vedaldi. 2023. Training-Free Layout Control with Cross-Attention Guidance. arXiv:2304.03373 [cs.CV] - · arXiv
  11. [12][12] Lydia B. Chilton, Savvas Petridis, and Maneesh Agrawala. 2019. VisiBlends: A Flexible Workflow for Visual Blends. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19) . Association for Computing Machinery, New York, NY, USA, 1-14. https: //doi.org/10.1145/3290605.3300402 - · DOI
  12. [14][14] Orestes Chouchoulas and A.K. Day. 2007. Design Exploration Using A Shape Grammar With A Genetic Algorithm. Open House International 32 (06 2007), 26-35. https://doi.org/10.1108/OHI-02-2007-B0004 - · DOI
  13. [15][15] John Joon Young Chung and Eytan Adar. 2023. Artinter: AI-Powered Boundary Objects for Commissioning Visual Arts. In Proceedings of the 2023 ACM Designing Interactive Systems Conference (Pittsburgh, PA, USA) (DIS '23) . Association for Computing Machinery, New York, NY, USA, 1997-2018. https://doi.org/10.1145/ 3563657.3595961 -
  14. [16][16] John Joon Young Chung and Eytan Adar. 2023. PromptPaint: Steering Text-toImage Generation Through Paint Medium-like Interactions. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (, San Francisco, CA, USA,) (UIST '23) . Association for Computing Machinery, New York, NY, USA, Article 6, 17 pages. https://doi.org/10.1145/3586183.3606777 - · DOI
  15. [17][17] John Joon Young Chung, Shiqing He, and Eytan Adar. 2021. The Intersection of Users, Roles, Interactions, and Technologies in Creativity Support Tools. In Proceedings of the 2021 ACM Designing Interactive Systems Conference (Virtual Event, USA) (DIS '21) . Association for Computing Machinery, New York, NY, USA, 1817-1833. https://doi.org/10.1145/3461778.3462050 - · DOI
  16. [18][18] John Joon Young Chung, Shiqing He, and Eytan Adar. 2022. Artist Support Networks: Implications for Future Creativity Support Tools. In Proceedings of the 2022 ACM Designing Interactive Systems Conference (Virtual Event, Australia) (DIS '22) . Association for Computing Machinery, New York, NY, USA, 232-246. https://doi.org/10.1145/3532106.3533505 - · DOI · Paper page
  17. [19][19] Nigel Cross. 1997. Descriptive models of creative design: application to an example. Design Studies 18, 4 (1997), 427-440. https://doi.org/10.1016/S0142694X(97)00010-0 Descriptive models of design. - · DOI
  18. [22][22] Claudia Eckert and Martin Stacey. 2000. Sources of inspiration: a language of design. Design studies 21, 5 (2000), 523-538. -
  19. [23][23] Jennifer Fernquist, Tovi Grossman, and George Fitzmaurice. 2011. Sketch-sketch revolution: an engaging tutorial system for guided sketching and application learning. In Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology (Santa Barbara, California, USA) (UIST '11) . Association for Computing Machinery, New York, NY, USA, 373-382. https://doi.org/10. 1145/2047196.2047245 -
  20. [24][24] Jonas Frich, Michael Mose Biskjaer, Lindsay MacDonald Vermeulen, Christian Remy, and Peter Dalsgaard. 2019. Strategies in Creative Professionals' Use of Digital Tools Across Domains. In Proceedings of the 2019 Conference on Creativity and Cognition (San Diego, CA, USA) (C&C '19) . Association for Computing Machinery, New York, NY, USA, 210-221. https://doi.org/10.1145/3325480.3325494 - · DOI
  21. [26][26] Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, and Daniel Cohen-Or. 2022. An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. arXiv:2208.01618 [cs.CV] - · arXiv
  22. [27][27] Steve Garner and Deana McDonagh-Philp. 2001. Problem interpretation and resolution via visual stimuli: the use of 'mood boards' in design education. Journal of Art & Design Education 20, 1 (2001), 57-64. -
  23. [28][28] Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2016. Image Style Transfer Using Convolutional Neural Networks. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) . 2414-2423. https://doi.org/10. 1109/CVPR.2016.265 -
  24. [29][29] A.K. Goel. 1997. Design, analogy, and creativity. IEEE Expert 12, 3 (1997), 62-70. https://doi.org/10.1109/64.590078 - · DOI
  25. [31][31] Scarlett R. Herring, Chia-Chen Chang, Jesse Krantzler, and Brian P. Bailey. 2009. Getting Inspired! Understanding How and Why Examples Are Used in Creative Design Practice. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, USA) (CHI '09) . Association for Computing Machinery, New York, NY, USA, 87-96. https://doi.org/10.1145/1518701.1518717 - · DOI
  26. [32][32] Barbara Hirst. 1992. How artists overcome creative blocks. The Journal of Creative Behavior (1992). -
  27. [33][33] Josh Holinaty, Alec Jacobson, and Fanny Chevalier. 2021. Supporting Reference Imagery for Digital Drawing. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops . 2434-2442. -
  28. [34][34] Keith J Holyoak and Paul Thagard. 1996. Mental leaps: Analogy in creative thought . MIT press. -
  29. [35][35] Tom Hope, Ronen Tamari, Daniel Hershcovich, Hyeonsu B Kang, Joel Chan, Aniket Kittur, and Dafna Shahaf. 2022. Scaling Creative Inspiration with FineGrained Functional Aspects of Ideas. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22) . Association for Computing Machinery, New York, NY, USA, Article 12, 15 pages. https://doi.org/10.1145/3491102.3517434 - · DOI
  30. [36][36] Alexander Ivanov, David Ledo, Tovi Grossman, George Fitzmaurice, and Fraser Anderson. 2022. MoodCubes: Immersive Spaces for Collecting, Discovering and Envisioning Inspiration Materials. In Proceedings of the 2022 ACM Designing Interactive Systems Conference (Virtual Event, Australia) (DIS '22) . Association for Computing Machinery, New York, NY, USA, 189-203. https://doi.org/10.1145/ 3532106.3533565 -
  31. [37][37] David G Jansson and Steven M Smith. 1991. Design fixation. Design studies 12, 1 (1991), 3-11. -
  32. [38][38] Youngseung Jeon, Seungwan Jin, Patrick C. Shih, and Kyungsik Han. 2021. FashionQ: An AI-Driven Creativity Support Tool for Facilitating Ideation in Fashion Design. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI '21) . Association for Computing Machinery, New York, NY, USA, Article 576, 18 pages. https://doi.org/10.1145/3411764.3445093 - · DOI · Paper page
  33. [39][39] Youwen Kang, Zhida Sun, Sitong Wang, Zeyu Huang, Ziming Wu, and Xiaojuan Ma. 2021. MetaMap: Supporting Visual Metaphor Ideation through MultiDimensional Example-Based Exploration. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI '21) . Association for Computing Machinery, New York, NY, USA, Article 427, 15 pages. https://doi.org/10.1145/3411764.3445325 - · DOI
  34. [40][40] Pegah Karimi, Nicholas Davis, Mary Lou Maher, Kazjon Grace, and Lina Lee. 2019. Relating Cognitive Models of Design Creativity to the Similarity of Sketches Generated by an AI Partner. In Proceedings of the 2019 Conference on Creativity and Cognition (San Diego, CA, USA) (C&C '19) . Association for Computing Machinery, New York, NY, USA, 259-270. https://doi.org/10.1145/3325480.3325488 - · DOI
  35. [41][41] Pegah Karimi, Jeba Rezwana, Safat Siddiqui, Mary Lou Maher, and Nasrin Dehbozorgi. 2020. Creative Sketching Partner: An Analysis of Human-AI Co-Creativity. In Proceedings of the 25th International Conference on Intelligent User Interfaces (Cagliari, Italy) (IUI '20) . Association for Computing Machinery, New York, NY, USA, 221-230. https://doi.org/10.1145/3377325.3377522 - · DOI
  36. [43][43] Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila. 2020. Analyzing and Improving the Image Quality of StyleGAN. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . -
  37. [44][44] Andruid Kerne. 2000. CollageMachine: An Interactive Agent of Web Recombination. Leonardo 33, 5 (10 2000), 347-350. https: //doi.org/10.1162/002409400552801 arXiv:https://direct.mit.edu/leon/articlepdf/33/5/347/1570572/002409400552801.pdf - · DOI
  38. [45][45] Kevin Gonyop Kim, Richard Lee Davis, Alessia Eletta Coppi, Alberto Cattaneo, and Pierre Dillenbourg. 2022. Mixplorer: Scaffolding Design Space Exploration through Genetic Recombination of Multiple Peoples' Designs to Support Novices' Creativity. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22) . Association for Computing Machinery, New York, NY, USA, Article 308, 13 pages. https://doi.org/10.1145/3491102.3501854 - · DOI
  39. [48][48] Janin Koch, Andrés Lucero, Lena Hegemann, and Antti Oulasvirta. 2019. May AI? Design Ideation with Cooperative Contextual Bandits. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19) . Association for Computing Machinery, New York, NY, USA, 1-12. https://doi.org/10.1145/3290605.3300863 - · DOI
  40. [49][49] Janin Koch, Nicolas Taffin, Andrés Lucero, and Wendy E. Mackay. 2020. SemanticCollage: Enriching Digital Mood Board Design with Semantic Labels. In Proceedings of the 2020 ACM Designing Interactive Systems Conference (Eindhoven, Netherlands) (DIS '20) . Association for Computing Machinery, New York, NY, USA, 407-418. https://doi.org/10.1145/3357236.3395494 - · DOI
  41. [53][53] Seungwoo Lee, Chaerin Kong, Donghyeon Jeon, and Nojun Kwak. 2023. AADiff: Audio-Aligned Video Synthesis with Text-to-Image Diffusion. arXiv:2305.04001 [cs.CV] - · arXiv
  42. [54][54] Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023. BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models. arXiv:2301.12597 [cs.CV] - · arXiv
  43. [55][55] Yuheng Li, Haotian Liu, Qingyang Wu, Fangzhou Mu, Jianwei Yang, Jianfeng Gao, Chunyuan Li, and Yong Jae Lee. 2023. GLIGEN: Open-Set Grounded Textto-Image Generation. CVPR (2023). -
  44. [56][56] Long Lian, Boyi Li, Adam Yala, and Trevor Darrell. 2023. LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models. arXiv:2305.13655 [cs.CV] - · arXiv
  45. [57][57] Vivian Liu, Jo Vermeulen, George Fitzmaurice, and Justin Matejka. 2023. 3DALLE: Integrating Text-to-Image AI in 3D Design Workflows. In Proceedings of the 2023 ACM Designing Interactive Systems Conference (Pittsburgh, PA, USA) (DIS '23) . Association for Computing Machinery, New York, NY, USA, 1955-1977. https://doi.org/10.1145/3563657.3596098 - · DOI
  46. [58][58] Andrés Lucero. 2015. Funky-Design-Spaces: Interactive Environments for Creativity Inspired by Observing Designers Making Mood Boards. In Human-Computer Interaction - INTERACT 2015 , Julio Abascal, Simone Barbosa, Mirko Fetter, Tom Gross, Philippe Palanque, and Marco Winckler (Eds.). Springer International Publishing, Cham, 474-492. -
  47. [59][59] Andrés Lucero, Dzmitry Aliakseyeu, Kees Overbeeke, and Jean-Bernard Martens. 2009. An Interactive Support Tool to Convey the Intended Message in Asynchronous Presentations. In Proceedings of the International Conference on Advances in Computer Entertainment Technology (Athens, Greece) (ACE '09) . Association for Computing Machinery, New York, NY, USA, 11-18. https://doi.org/10.1145/ 1690388.1690391 -
  48. [60][60] Justin Matejka, Michael Glueck, Erin Bradner, Ali Hashemi, Tovi Grossman, and George Fitzmaurice. 2018. Dream Lens: Exploration and Visualization of Large-Scale Generative Design Datasets. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18) . Association for Computing Machinery, New York, NY, USA, 1-12. https://doi.org/10.1145/3173574.3173943 - · DOI · Paper page
  49. [61][61] Chong Mou, Xintao Wang, Liangbin Xie, Yanze Wu, Jian Zhang, Zhongang Qi, Ying Shan, and Xiaohu Qie. 2023. T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models. arXiv:2302.08453 [cs.CV] - · arXiv
  50. [62][62] Felix Müller-Wienbergen, Oliver Müller, Stefan Seidel, and Jörg Becker. 2011. Leaving the beaten tracks in creative work-A design theory for systems that support convergent and divergent thinking. Journal of the Association for Information Systems 12, 11 (2011), 2. -
  51. [63][63] Michael D Mumford, Michele I Mobley, Roni Reiter-Palmon, Charles E Uhlman, and Lesli M Doares. 1991. Process analytic models of creative capacities. Creativity research journal 4, 2 (1991), 91-122. https://doi.org/10.1080/10400419209534428 arXiv:https://doi.org/10.1080/10400419209534428 - · DOI
  52. [64][64] Yukari Nagai, Toshiharu Taura, and Futoshi Mukai. 2009. Concept blending and dissimilarity: factors for creative concept generation process. Design Studies 30, 6 (2009), 648-675. https://doi.org/10.1016/j.destud.2009.05.004 - · DOI
  53. [65][65] Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob Mcgrew, Ilya Sutskever, and Mark Chen. 2022. GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. In Proceedings of the 39th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 162) , Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvari, Gang Niu, and Sivan Sabato (Eds.). PMLR, 16784-16804. https://proceedings.mlr.press/v162/nichol22a.html -
  54. [66][66] Changhoon Oh, Jungwoo Song, Jinhan Choi, Seonghyeon Kim, Sungwoo Lee, and Bongwon Suh. 2018. I Lead, You Help but Only with Enough Details: Understanding User Experience of Co-Creation with Artificial Intelligence. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18) . Association for Computing Machinery, New York, NY, USA, 1-13. https://doi.org/10.1145/3173574.3174223 - · DOI · Paper page
  55. [67][67] OpenAI. 2020. Language Models are Few-Shot Learners. arXiv:2005.14165 [cs.CL] - · arXiv
  56. [68][68] OpenAI. 2023. GPT-4 Technical Report. arXiv:2303.08774 [cs.CL] - · arXiv
  57. [70][70] Marcin L. Pilat and Christian Jacob. 2008. Creature Academy: A system for virtual creature evolution. In 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence) . 3289-3297. https://doi.org/10. 1109/CEC.2008.4631243 -
  58. [71][71] Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021. Learning Transferable Visual Models From Natural Language Supervision. In Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 8748-8763. https://proceedings.mlr.press/v139/radford21a.html -
  59. [72][72] Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022. Hierarchical Text-Conditional Image Generation with CLIP Latents. arXiv:2204.06125 [cs.CV] - · arXiv
  60. [73][73] Daniel Ritchie, Ankita Arvind Kejriwal, and Scott R. Klemmer. 2011. D.Tour: Style-Based Exploration of Design Example Galleries. In Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology (Santa Barbara, California, USA) (UIST '11) . Association for Computing Machinery, New York, NY, USA, 165-174. https://doi.org/10.1145/2047196.2047216 - · DOI
  61. [75][75] Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman. 2023. DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 22500-22510. -
  62. [78][78] Pao Siangliulue, Joel Chan, Krzysztof Z. Gajos, and Steven P. Dow. 2015. Providing Timely Examples Improves the Quantity and Quality of Generated Ideas. In Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition (Glasgow, United Kingdom) (C&C '15) . Association for Computing Machinery, New York, NY, USA, 83-92. https://doi.org/10.1145/2757226.2757230 - · DOI · Paper page
  63. [79][79] Dean Keith Simonton. 2003. Scientific creativity as constrained stochastic behavior: the integration of product, person, and process perspectives. Psychological bulletin 129, 4 (2003), 475. -
  64. [80][80] Evgeny Stemasov, David Ledo, George Fitzmaurice, and Fraser Anderson. 2023. Immersive Sampling: Exploring Sampling for Future Creative Practices in MediaRich, Immersive Spaces. In Proceedings of the 2023 ACM Designing Interactive Systems Conference (Pittsburgh, PA, USA) (DIS '23) . Association for Computing Machinery, New York, NY, USA, 212-229. https://doi.org/10.1145/3563657.3596131 - · DOI
  65. [81][81] Kim Sung-Bin, Arda Senocak, Hyunwoo Ha, Andrew Owens, and Tae-Hyun Oh. 2023. Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 6430-6440. -
  66. [82][82] Michela Turrin, Peter von Buelow, and Rudi Stouffs. 2011. Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms. Advanced Engineering Informatics 25, 4 (2011), 656675. https://doi.org/10.1016/j.aei.2011.07.009 Special Section: Advances and Challenges in Computing in Civil and Building Engineering. - · DOI
  67. [84][84] Sitong Wang, Savvas Petridis, Taeahn Kwon, Xiaojuan Ma, and Lydia B Chilton. 2023. PopBlends: Strategies for Conceptual Blending with Large Language Models. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (Hamburg, Germany) (CHI '23) . Association for Computing Machinery, New York, NY, USA, Article 435, 19 pages. https://doi.org/10.1145/3544548.3580948 - · DOI · Paper page
  68. [85][85] Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou. 2020. MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of PreTrained Transformers. In Advances in Neural Information Processing Systems , H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 5776-5788. https://proceedings.neurips.cc/paper\_files/ paper/2020/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf -
  69. [86][86] Tongshuang Wu, Michael Terry, and Carrie Jun Cai. 2022. AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Prompts. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) (CHI '22) . Association for Computing Machinery, New York, NY, USA, Article 385, 22 pages. https://doi.org/10.1145/3491102. 3517582 - · DOI
  70. [87][87] Lixiu Yu and Jeffrey V. Nickerson. 2011. Cooks or Cobblers? Crowd Creativity through Combination. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, BC, Canada) (CHI '11) . Association for Computing Machinery, New York, NY, USA, 1393-1402. https: //doi.org/10.1145/1978942.1979147 - · DOI
  71. [88][88] Loutfouz Zaman, Wolfgang Stuerzlinger, Christian Neugebauer, Rob Woodbury, Maher Elkhaldi, Naghmi Shireen, and Michael Terry. 2015. GEM-NI: A System for Creating and Managing Alternatives In Generative Design. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (Seoul, Republic of Korea) (CHI '15) . Association for Computing Machinery, New York, NY, USA, 1201-1210. https://doi.org/10.1145/2702123.2702398 - · DOI · Paper page
  72. [89][89] Enhao Zhang and Nikola Banovic. 2021. Method for Exploring Generative Adversarial Networks (GANs) via Automatically Generated Image Galleries. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI '21) . Association for Computing Machinery, New York, NY, USA, Article 76, 15 pages. https://doi.org/10.1145/3411764.3445714 - · DOI
  73. [91][91] Nanxuan Zhao, Nam Wook Kim, Laura Mariah Herman, Hanspeter Pfister, Rynson W.H. Lau, Jose Echevarria, and Zoya Bylinskii. 2020. ICONATE: Automatic Compound Icon Generation and Ideation. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI '20) . Association for Computing Machinery, New York, NY, USA, 1-13. https://doi.org/10.1145/3313831.3376618 - · DOI
  74. [92][92] Guangcong Zheng, Xianpan Zhou, Xuewei Li, Zhongang Qi, Ying Shan, and Xi Li. 2023. LayoutDiffusion: Controllable Diffusion Model for Layout-to-Image Generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 22490-22499. -

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Authors
Choi, D., Hong, S., Park, J., Chung, J. J. Y., & Kim, J.
Affiliations
  • Korea Advanced Institute of Science and Technology (KR)
  • Seoul National University of Science and Technology (KR)
  • Daegu Gyeongbuk Institute of Science and Technology (KR)
  • Midjourney, United States
ORCID
Venue
Proceedings of the CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2024-05-11
Pages
1-25
DOI
10.1145/3613904.3642794
OpenAlex
W4396831955
Cited by
124
References
12
Citations by year
2026: 49 · 2025: 67 · 2024: 8
FWCI
48.45
Type
conference paper
Language
en
Open access
Licence
Locations
  • CHI Conference on Human Factors in Computing Systems (publishedVersion, cc-by-nc-sa)
  • arXiv (Cornell University) (submittedVersion, cc-by)
  • arXiv (Cornell University) (cc-by)
Funders
Ministry of Science and ICT, South Korea (2019-0-00075,2021-0-01347)
Topics
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
  • Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
generative AI, creativity support, design sketches, design inspiration

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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