pith. sign in

arxiv: 2512.02288 · v2 · pith:FJICVJL2new · submitted 2025-12-02 · 💻 cs.HC

Artographer: a Curatorial Interface for Art Space Exploration

Shm Garanganao Almeda , John Joon Young Chung , Sophia Liu , Brett Halperin , Yuwen Lu , Bjoern Hartmann , Max Kreminski This is my paper

Pith reviewed 2026-05-21 17:29 UTC · model grok-4.3

classification 💻 cs.HC
keywords artographerdesigndistributionmediaartworkartworkscuratorialexplore
0
0 comments X

The pith

Artographer is a zoomable 2D embedding-based map for art exploration, evaluated in a study with 20 participants to surface values of Visibility, Agency, Serendipity, and Friction that challenge recommendation-driven media distribution.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The system turns a large collection of artworks into a single interactive map where similar pieces cluster together. Users can zoom in to see details, pan across the space, and collect items for a task or just to explore freely. Researchers ran a study with 20 people, nine of them art historians, who used the map both for directed collection tasks and open-ended browsing. From these sessions the team extracted four values that appeared in how people moved through and related to the artworks: seeing more of the collection at once, feeling in control of the path, encountering unexpected connections, and experiencing some resistance or effort that made the discovery feel meaningful. The paper argues these values point toward a curatorial style of interface rather than the narrow, personalized feeds that dominate current platforms.

Core claim

We identify values enacted in spatial art discovery (Visibility, Agency, Serendipity, Friction) and consider how these values challenge dominant design paradigms -- in particular, the recommendation systems governing contemporary media distribution platforms.

Load-bearing premise

That the particular embedding-based clustering and 2D projection used to build the map produces a spatial layout whose relationships are meaningful enough for participants to discover and articulate the claimed values during a short session.

Figures

Figures reproduced from arXiv: 2512.02288 by Bjoern Hartmann, Brett Halperin, John Joon Young Chung, Max Kreminski, Shm Garanganao Almeda, Sophia Liu, Yuwen Lu.

Figure 1
Figure 1. Figure 1: Artographer is an interface for exploring an intentionally curated dataset of ~16,000 historical artworks as an zoomable [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Each artwork is represented by a multimodal [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Artographer (left) is a spatial map interface for historical artwork exploration. Our Baseline system (right) was a [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: While participants collected a similar number of artworks (around 8-13) regardless of system, they interacted with significantly more artworks (around 80 vs. around 21) when using Artographer to complete the task (p < 0.001 in both conditions) [PITH_FULL_IMAGE:figures/full_fig_p007_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Comparing the number of images each participant [PITH_FULL_IMAGE:figures/full_fig_p007_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: We logged the 2D coordinates of every event where [PITH_FULL_IMAGE:figures/full_fig_p008_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: P7’s exploration trajectory during the targeted col [PITH_FULL_IMAGE:figures/full_fig_p008_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: P3, P8, and P9 each described themselves as personally interested in graphic design and abstract art. During the free [PITH_FULL_IMAGE:figures/full_fig_p009_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Participants collected a disproportionate number [PITH_FULL_IMAGE:figures/full_fig_p010_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: This table compares how three kinds of Curatorial [PITH_FULL_IMAGE:figures/full_fig_p011_11.png] view at source ↗
read the original abstract

Relating a piece to previously established works is crucial in creating and engaging with art, but AI interfaces tend to obscure such relationships, rather than helping users explore them. Embedding models present new opportunities to support spatially exploring and relating artwork. We built Artographer, an art-exploration system featuring a zoomable 2-D map, constructed from similarity-clustered embeddings of ~16,000 historical artworks. We used Artographer as a design probe to explore how alternative artwork distribution interface design can shape media engagement: we invited 20 participants, including 9 art history scholars, to traverse the map, collecting artworks for a goal-driven task and while freely exploring. We identify values enacted in spatial art discovery (Visibility, Agency, Serendipity, Friction) and consider how these values challenge dominant design paradigms -- in particular, the recommendation systems governing contemporary media distribution platforms. We reimagine a curatorial approach to media distribution, within digital ecosystems where history and culture can thrive.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript presents Artographer, a zoomable 2-D map interface for exploring ~16,000 historical artworks derived from similarity-clustered embeddings. The system is used as a design probe in a qualitative study with 20 participants (including 9 art-history scholars) who complete goal-driven collection tasks and free exploration sessions. From observed behaviors and participant articulations, the authors identify four values enacted by spatial art discovery—Visibility, Agency, Serendipity, and Friction—and argue that these values challenge recommendation-system paradigms in contemporary media platforms, advocating instead for curatorial approaches to digital cultural distribution.

Significance. If the central claims hold, the work contributes concrete evidence that spatial, embedding-based interfaces can surface historically grounded relationships and promote reflective engagement with art, offering a counterpoint to opaque recommendation engines. The participation of domain experts lends credibility to the identified values and supplies a useful case study for HCI research on alternative media-distribution designs.

major comments (2)
  1. [System description] System description (map-construction paragraph): the manuscript states that the 2-D map is built from 'similarity-clustered embeddings' of ~16k artworks but supplies neither the embedding model identity, the clustering algorithm, the dimensionality-reduction method, nor any quantitative or human validation that the resulting proximities and clusters correspond to art-historical or curatorial relations rather than embedding artifacts. Because the four values are claimed to be enacted specifically by the spatial layout, this missing grounding is load-bearing for the central argument.
  2. [Study procedure and analysis] Study procedure and analysis section: the abstract and methods narrative give no information on the qualitative analysis approach (e.g., thematic analysis protocol), inter-rater reliability, or how participant statements were linked to the four values. Without these details it is difficult to assess whether the reported values are robustly supported by the data or could arise from any navigable 2-D canvas.
minor comments (2)
  1. [Abstract] The abstract would benefit from a one-sentence statement of the analysis method and a brief note on map-construction choices to allow readers to evaluate the claims at a glance.
  2. [Figures] Figure captions for the map screenshots should explicitly state the embedding source and projection technique so that readers can judge the spatial relationships shown.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed feedback. The comments highlight important areas for improving technical transparency and methodological rigor, which we will address through targeted revisions to strengthen the manuscript's claims.

read point-by-point responses

  1. Referee: [System description] System description (map-construction paragraph): the manuscript states that the 2-D map is built from 'similarity-clustered embeddings' of ~16k artworks but supplies neither the embedding model identity, the clustering algorithm, the dimensionality-reduction method, nor any quantitative or human validation that the resulting proximities and clusters correspond to art-historical or curatorial relations rather than embedding artifacts. Because the four values are claimed to be enacted specifically by the spatial layout, this missing grounding is load-bearing for the central argument.

    Authors: We agree that these technical details are necessary to substantiate that the spatial proximities reflect art-historical relations rather than artifacts. In the revised manuscript we will expand the system description paragraph to name the specific embedding model, clustering algorithm, dimensionality-reduction method, and any validation procedures (quantitative or human) used to confirm the layout's alignment with curatorial relations. This addition will directly support the argument that the identified values arise from the embedding-based spatial organization. revision: yes

  2. Referee: [Study procedure and analysis] Study procedure and analysis section: the abstract and methods narrative give no information on the qualitative analysis approach (e.g., thematic analysis protocol), inter-rater reliability, or how participant statements were linked to the four values. Without these details it is difficult to assess whether the reported values are robustly supported by the data or could arise from any navigable 2-D canvas.

    Authors: We accept that the current methods narrative lacks sufficient detail on the analysis process. We will revise the study procedure and analysis section to specify the thematic analysis protocol, coding procedures, any inter-rater reliability assessment, and the explicit mapping from participant statements to the four values. To address the possibility that similar values could emerge from any 2-D canvas, we will add clarification in the discussion that the values are tied to the embedding-derived clusters and historical relationships surfaced by the map, supported by examples from the data where participants referenced specific proximities and serendipitous discoveries within art-historical groupings. revision: yes

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is an empirical HCI design-probe paper with no mathematical derivations, so it introduces no free parameters, axioms, or invented entities.

pith-pipeline@v0.9.0 · 5719 in / 1138 out tokens · 53945 ms · 2026-05-21T17:29:34.089623+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. "When to Hand Off, When to Work Together": Expanding Human-Agent Co-Creative Collaboration through Concurrent Interaction

    cs.HC 2026-03 unverdicted novelty 6.0

    Concurrent human-agent interactions occur in 31.8% of turns and follow five action patterns explained by six triggers and four enabling factors, enabled by a context-aware design probe called CLEO.

Reference graph

Works this paper leans on

71 extracted references · 71 canonical work pages · cited by 1 Pith paper

  1. [1]

    Shm Garanganao Almeda, Joy O Kim, and Bjoern Hartmann. 2025. Creativity Supportive Ecosystems: A Framework for Understanding Function and Disrup- tion in Online Art Worlds. InProceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25). Association for Computing Machinery, New York, NY, USA, 1–17. doi:10.1145/3706598.3713734

    work page doi:10.1145/3706598.3713734 2025

  2. [2]

    Chia Amisola. 2024. Becoming hypertext. https://everythingi.love

    work page 2024

  3. [3]

    Ran An. 2024. Art curation in virtual spaces: The influence of digital technology in redefining the aesthetics and interpretation of art | Humanities, Arts and Social Sciences Studies.Humanities, Arts and Social Sciences Studies(Aug. 2024). doi:10.69598/hasss.24.2.267552

    work page doi:10.69598/hasss.24.2.267552 2024

  4. [4]

    Artsy. 2025. Artsy/The-Art-Genome-Project. https://github.com/artsy/the-art- genome-project/tree/master

    work page 2025

  5. [5]

    Avgousti, G

    A. Avgousti, G. Papaioannou, and S. Hermon. 2024. Enhancing Online Acces- sibility of Digitized Artifacts from Small Museum Collections in Cyprus: An Empirical Evaluation of the CyprusArk Solution.J. Comput. Cult. Herit.17, 3 (April 2024), 34:1–34:24. doi:10.1145/3648229

    work page doi:10.1145/3648229 2024

  6. [6]

    Yaniv Bar, Noga Levy, and Lior Wolf. 2015. Classification of Artistic Styles Using Binarized Features Derived from a Deep Neural Network. InComputer Vision - ECCV 2014 Workshops, Lourdes Agapito, Michael M. Bronstein, and Carsten Rother (Eds.). Springer International Publishing, Cham, 71–84. doi:10.1007/978- 3-319-16178-5_5

    work page doi:10.1007/978- 2015

  7. [7]

    Shaowen Bardzell. 2010. Feminist HCI: taking stock and outlining an agenda for design. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’10). Association for Computing Machinery, New York, NY, USA, 1301–1310. doi:10.1145/1753326.1753521

    work page doi:10.1145/1753326.1753521 2010

  8. [8]

    Romain Beaumont and Christoph Schuhman. 2022. LAION-AI/aesthetic- predictor. https://github.com/LAION-AI/aesthetic-predictor original-date: 2022- 05-21T12:36:24Z

    work page 2022

  9. [9]

    Howard S. Becker. 1974. Art As Collective Action.American Sociological Review 39, 6 (1974), 767–776. doi:10.2307/2094151 Publisher: [American Sociological Association, Sage Publications, Inc.]

    work page doi:10.2307/2094151 1974

  10. [10]

    Bederson and James D

    Benjamin B. Bederson and James D. Hollan. 1994. Pad++: a zooming graphical interface for exploring alternate interface physics. InProceedings of the 7th Annual ACM Symposium on User Interface Software and Technology(Marina del Rey, California, USA)(UIST ’94). Association for Computing Machinery, New York, NY, USA, 17–26. doi:10.1145/192426.192435 Conferen...

    work page doi:10.1145/192426.192435 1994

  11. [11]

    Virginia Braun and Victoria Clarke. 2019. Reflecting on reflexive thematic analysis.Qualitative Research in Sport, Exercise and Health11, 4 (Aug. 2019), 589–597. doi:10.1080/2159676X.2019.1628806 Publisher: Routledge _eprint: https://doi.org/10.1080/2159676X.2019.1628806

    work page doi:10.1080/2159676x.2019.1628806 2019

  12. [12]

    Harriet R Cameron and Velvet Spors. 2023. The Museum is Dreaming: Re- Imagining the Museum through Feminist Values and Data Practices in Design Fiction. InProceedings of the 26th International Academic Mindtrek Conference (Mindtrek ’23). Association for Computing Machinery, New York, NY, USA, 182–

    work page 2023

  13. [13]

    doi:10.1145/3616961.3616984

    work page doi:10.1145/3616961.3616984

  14. [14]

    1999.Readings in Information Visualization: Using Vision to Think

    Stuart K Card, Jock D Mackinlay, and Ben Shneiderman. 1999.Readings in Information Visualization: Using Vision to Think. Morgan Kaufman

    work page 1999

  15. [15]

    Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, and Eric Wallace. 2023. Extracting training data from diffusion models. InProceedings of the 32nd USENIX Conference on Security Symposium (SEC ’23). USENIX Association, USA, 5253–5270

    work page 2023

  16. [16]

    Tara Chari and Lior Pachter. 2023. The specious art of single-cell genomics.PLOS Computational Biology19, 8 (2023), e1011288

    work page 2023

  17. [17]

    2006.Constructing Grounded Theory: A Practical Guide through Qualitative Analysis

    Kathy Charmaz. 2006.Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. SAGE. Google-Books-ID: 2ThdBAAAQBAJ

    work page 2006

  18. [18]

    Erin Cherry and Celine Latulipe. 2014. Quantifying the Creativity Support of Digital Tools through the Creativity Support Index.ACM Trans. Comput.-Hum. Interact.21, 4 (June 2014), 21:1–21:25. doi:10.1145/2617588

    work page doi:10.1145/2617588 2014

  19. [19]

    John Joon Young Chung, Shiqing He, and Eytan Adar. 2022. Artist Support Networks: Implications for Future Creativity Support Tools. InProceedings of the 2022 ACM Designing Interactive Systems Conference (DIS ’22). Association for Computing Machinery, New York, NY, USA, 232–246. doi:10.1145/3532106. 3533505

    work page doi:10.1145/3532106 2022

  20. [20]

    John Joon Young Chung and Max Kreminski. 2024. Patchview: LLM-powered Worldbuilding with Generative Dust and Magnet Visualization. InProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (Pittsburgh, PA, USA)(UIST ’24). Association for Computing Machinery, New York, NY, USA, Article 77, 19 pages. doi:10.1145/3654777.3676352

    work page doi:10.1145/3654777.3676352 2024

  21. [21]

    Marshall, Dick van Dijk, and Fiona McDermott

    Luigina Ciolfi, Gabriela Avram, Laura Maye, Nick Dulake, Mark T. Marshall, Dick van Dijk, and Fiona McDermott. 2016. Articulating Co-Design in Museums: Reflections on Two Participatory Processes. InProceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (CSCW ’16). Association for Computing Machinery, New York, NY,...

    work page arXiv 2016

  22. [22]

    Andy Coenen and Adam Pearce. [n. d.]. Understanding UMAP. https://pair- code.github.io/understanding-umap/

    work page

  23. [23]

    Kate Compton and Michael Mateas. 2015. Casual creators. InInternational Conference on Computational Creativity. 228–235

    work page 2015

  24. [24]

    Fass, Eric A

    Adam M. Fass, Eric A. Bier, and Eyton Adar. 2000. PicturePiper: using a re- configurable pipeline to find images on the Web. InProceedings of the 13th Annual ACM Symposium on User Interface Software and Technology(San Diego, California, USA)(UIST ’00). Association for Computing Machinery, New York, NY, USA, 51–62. doi:10.1145/354401.354411

    work page doi:10.1145/354401.354411 2000

  25. [25]

    Sarah Frost, Manu Mathew Thomas, and Angus G. Forbes. 2019. Art I Don’t Like: An Anti-Recommender System for Visual Art. Boston, MA. https://mw19.mwconf.org/proposal/art-i-dont-like-an-anti-recommender- system-for-visual-art/index.html

    work page 2019

  26. [26]

    Tim Gorichanaz. 2020. Engaging with Public Art: An Exploration of the Design Space. InProceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20). Association for Computing Machinery, New York, NY, USA, 1–14. doi:10.1145/3313831.3376640

    work page doi:10.1145/3313831.3376640 2020

  27. [27]

    Katherine Isbister, Kristina Höök, Michael Sharp, and Jarmo Laaksolahti. 2006. The sensual evaluation instrument: developing an affective evaluation tool. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’06). Association for Computing Machinery, New York, NY, USA, 1163–1172. doi:10.1145/1124772.1124946

    work page doi:10.1145/1124772.1124946 2006

  28. [28]

    Hyeon Jeon, Hyunwook Lee, Yun-Hsin Kuo, Taehyun Yang, Daniel Archambault, Sungahn Ko, Takanori Fujiwara, Kwan-Liu Ma, and Jinwook Seo. 2025. Unveil- ing High-dimensional Backstage: A Survey for Reliable Visual Analytics with Dimensionality Reduction. InProceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25). Association for ...

    work page doi:10.1145/3706598.3713551 2025

  29. [29]

    Suzanne Kobeisse and Lars Erik Holmquist. 2023. Moving Inside the Box: In- teracting with Interpretation of Historical Artefacts Through Tangible Aug- mented Reality. InACM Multimedia Asia 2023. ACM, Tainan Taiwan, 1–7. doi:10.1145/3595916.3626408

    work page doi:10.1145/3595916.3626408 2023

  30. [30]

    Karen Johanne Kortbek and Kaj Grønbæk. 2008. Communicating art through interactive technology: new approaches for interaction design in art museums. In Proceedings of the 5th Nordic conference on Human-computer interaction: building bridges (NordiCHI ’08). Association for Computing Machinery, New York, NY, USA, 229–238. doi:10.1145/1463160.1463185

    work page doi:10.1145/1463160.1463185 2008

  31. [31]

    Max Kreminski, Isaac Karth, Michael Mateas, and Noah Wardrip-Fruin. 2022. Evaluating Mixed-Initiative Creative Interfaces via Expressive Range Coverage Analysis. InJoint Proceedings of the ACM IUI Workshops 2022. ACM, Helsinki, FInland. https://mkremins.github.io/publications/ERaCA_HAI-GEN2022.pdf

    work page 2022

  32. [32]

    John Lamping, Ramana Rao, and Peter Pirolli. 1995. A focus+context technique based on hyperbolic geometry for visualizing large hierarchies. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems(Denver, Colorado, USA)(CHI ’95). ACM Press/Addison-Wesley Publishing Co., USA, 401–408. doi:10. 1145/223904.223956

    work page arXiv 1995

  33. [33]

    Jerrold Levinson. 1979. DEFINING ART HISTORICALLY.The British Journal of Aesthetics19, 3 (Jan. 1979), 232–250. doi:10.1093/bjaesthetics/19.3.232

    work page doi:10.1093/bjaesthetics/19.3.232 1979

  34. [34]

    Jerrold Levinson. 1989. Refining Art Historically.The Journal of Aesthetics and Art Criticism47, 1 (1989), 21–33. doi:10.2307/431990 Publisher: [Wiley, American Society for Aesthetics]

    work page doi:10.2307/431990 1989

  35. [35]

    Jingyi Li, Eric Rawn, Jacob Ritchie, Jasper Tran O’Leary, and Sean Follmer. 2023. Beyond the Artifact: Power as a Lens for Creativity Support Tools. InProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST ’23). Association for Computing Machinery, New York, NY, USA, 1–15. doi:10.1145/3586183.3606831

    work page doi:10.1145/3586183.3606831 2023

  36. [36]

    Weiwei Li. 2025. Enhanced automated art curation using supervised modified CNN for art style classification.Scientific Reports15, 1 (March 2025), 7319. doi:10.1038/s41598-025-91671-z Publisher: Nature Publishing Group

    work page doi:10.1038/s41598-025-91671-z 2025

  37. [37]

    Ryan Louie, Jesse Engel, and Cheng-Zhi Anna Huang. 2022. Expressive Commu- nication: Evaluating Developments in Generative Models and Steering Interfaces for Music Creation. InProceedings of the 27th International Conference on Intelli- gent User Interfaces (IUI ’22). Association for Computing Machinery, New York, NY, USA, 405–417. doi:10.1145/3490099.3511159

    work page doi:10.1145/3490099.3511159 2022

  38. [38]

    Mei Luo, Li Liu, Yue Lu, and Ching Y. Suen. 2025. Art style classification via self-supervised dual-teacher knowledge distillation.Applied Soft Computing174 (April 2025), 112964. doi:10.1016/j.asoc.2025.112964

    work page doi:10.1016/j.asoc.2025.112964 2025

  39. [39]

    Leland McInnes, John Healy, Nathaniel Saul, and Lukas Großberger. 2018. UMAP: Uniform Manifold Approximation and Projection.Journal of Open Source Software 3, 29 (Sept. 2018), 861. doi:10.21105/joss.00861

    work page doi:10.21105/joss.00861 2018

  40. [40]

    Christofer Meinecke, Chris Hall, and Stefan Jänicke. 2022. Towards Enhancing Virtual Museums by Contextualizing Art through Interactive Visualizations.J. Comput. Cult. Herit.15, 4 (Dec. 2022), 62:1–62:26. doi:10.1145/3527619

    work page doi:10.1145/3527619 2022

  41. [41]

    Louie Meyer, Johanne Engel Aaen, Anitamalina Regitse Tranberg, Peter Kun, Matthias Freiberger, Sebastian Risi, and Anders Sundnes Løvlie. 2024. Algorith- mic Ways of Seeing: Using Object Detection to Facilitate Art Exploration. In Proceedings of the CHI Conference on Human Factors in Computing Systems. ACM, Honolulu HI USA, 1–18. doi:10.1145/3613904.3642157

    work page doi:10.1145/3613904.3642157 2024

  42. [42]

    Murray, L

    N. Murray, L. Marchesotti, and F. Perronnin. 2012. AVA: A large-scale database for aesthetic visual analysis.2012 IEEE Conference on Computer Vision and Pattern Recognition(June 2012), 2408–2415. doi:10.1109/CVPR.2012.6247954 Conference Name: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ISBN: 9781467312288 9781467312264 978146731...

    work page doi:10.1109/cvpr.2012.6247954 2012

  43. [43]

    Nelson, Swen E

    Mark J. Nelson, Swen E. Gaudl, Simon Colton, and Sebastian Deterding. 2018. Curious users of casual creators. InProceedings of the 13th International Confer- ence on the Foundations of Digital Games (FDG ’18). Association for Computing Machinery, New York, NY, USA, 1–6. doi:10.1145/3235765.3235826

    work page doi:10.1145/3235765.3235826 2018

  44. [44]

    Daniela Petrelli and Sinead O’Brien. 2018. Phone vs. Tangible in Museums: A Comparative Study. InProceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–12. doi:10.1145/3173574.3173686

    work page doi:10.1145/3173574.3173686 2018

  45. [45]

    Mitchel Resnick, Brad Myers, Kumiyo Nakakoji, Ben Shneiderman, Randy Pausch, Ted Selker, and Mike Eisenberg. 2005. Design principles for tools to support creative thinking. InReport of Workshop on Creativity Support Tools

    work page 2005

  46. [46]

    Kimiko Ryokai, Noriko Misra, and Yoshinori Hara. 2015. Artistic Distance: Body Movements as Launching Points for Art Inquiry. InProceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ’15). Association for Computing Machinery, New York, NY, USA, 679–686. doi:10.1145/2702613.2702958

    work page doi:10.1145/2702613.2702958 2015

  47. [47]

    Lee, Jaakko Pelto- nen, Daniel Weiskopf, Stephen C

    Dominik Sacha, Leishi Zhang, Michael Sedlmair, John A. Lee, Jaakko Pelto- nen, Daniel Weiskopf, Stephen C. North, and Daniel A. Keim. 2017. Visual Interaction with Dimensionality Reduction: A Structured Literature Analysis. IEEE Transactions on Visualization and Computer Graphics23, 1 (2017), 241–250. doi:10.1109/TVCG.2016.2598495

    work page doi:10.1109/tvcg.2016.2598495 2017

  48. [48]

    2015.The Coding Manual for Qualitative Researchers

    Johnny Saldana. 2015.The Coding Manual for Qualitative Researchers. SAGE. Google-Books-ID: jh1iCgAAQBAJ

    work page 2015

  49. [49]

    Christoph Schuhmann. 2022. LAION-Aesthetics. https://laion.ai/blog/laion- aesthetics

    work page 2022

  50. [50]

    Christoph Schuhmann. 2025. christophschuhmann/improved-aesthetic-predictor. https://github.com/christophschuhmann/improved-aesthetic-predictor original- date: 2022-06-25T20:57:49Z

    work page 2025

  51. [51]

    Gillian Smith and Jim Whitehead. 2010. Analyzing the expressive range of a level generator. InProceedings of the 2010 Workshop on Procedural Content Generation in Games (PCGames ’10). Association for Computing Machinery, New York, NY, USA, 1–7. doi:10.1145/1814256.1814260

    work page doi:10.1145/1814256.1814260 2010

  52. [52]

    Koleva, Matt Adams, Ju Row Farr, Nick Tandavanitj, and Anders Sundnes Løvlie

    Jocelyn Spence, Benjamin Bedwell, Michelle Coleman, Steve Benford, Boriana N. Koleva, Matt Adams, Ju Row Farr, Nick Tandavanitj, and Anders Sundnes Løvlie. Artographer: a Curatorial Interface for Art Space Exploration Conference acronym ’XX, June 03–05, 2018, Woodstock, NY

    work page 2018

  53. [53]

    Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, and Eric Horvitz

    Seeing with New Eyes: Designing for In-the-Wild Museum Gifting. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–13. doi:10.1145/3290605.3300235

    work page doi:10.1145/3290605.3300235 2019

  54. [54]

    Ramya Srinivasan. 2024. To See or Not to See: Understanding the Tensions of Al- gorithmic Curation for Visual Arts. InProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency (FAccT ’24). Association for Computing Machinery, New York, NY, USA, 444–455. doi:10.1145/3630106.3658917

    work page doi:10.1145/3630106.3658917 2024

  55. [55]

    Sangho Suh, Meng Chen, Bryan Min, Toby Jia-Jun Li, and Haijun Xia. 2024. Luminate: Structured Generation and Exploration of Design Space with Large Language Models for Human-AI Co-Creation. InProceedings of the 2024 CHI Conference on Human Factors in Computing Systems(Honolulu, HI, USA)(CHI ’24). Association for Computing Machinery, New York, NY, USA, Art...

    work page doi:10.1145/3613904.3642400 2024

  56. [56]

    Sangho Suh, Bryan Min, Srishti Palani, and Haijun Xia. 2023. Sensecape: En- abling Multilevel Exploration and Sensemaking with Large Language Models. InProceedings 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 1, 18 pages. doi:10...

    work page doi:10.1145/3586183.3606756 2023

  57. [57]

    Talton, Daniel Gibson, Lingfeng Yang, Pat Hanrahan, and Vladlen Koltun

    Jerry O. Talton, Daniel Gibson, Lingfeng Yang, Pat Hanrahan, and Vladlen Koltun

    work page

  58. [58]

    Exploratory modeling with collaborative design spaces.ACM Trans. Graph. 28, 5 (Dec. 2009), 1–10. doi:10.1145/1618452.1618513

    work page doi:10.1145/1618452.1618513 2009

  59. [59]

    Michaela Tuscher, Velitchko Filipov, Teresa Kamencek, Raphael Rosen- berg, and Silvia Miksch. 2025. Nodes, Edges, and Artistic Wedges: A Survey on Network Visualization in Art History.Computer Graphics Forum44, 3 (2025), e70154. doi:10.1111/cgf.70154 _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/cgf.70154

    work page doi:10.1111/cgf.70154 2025

  60. [60]

    Alina Valyaeva. 2023. AI Image Statistics for 2024: How Much Content Was Created by AI. https://journal.everypixel.com/ai-image-statistics

    work page 2023

  61. [61]

    Elena Villaespesa. 2019. Museum Collections and Online Users: Development of a Segmentation Model for the Metropolitan Museum of Art.Visitor Studies22, 2 (July 2019), 233–252. doi:10.1080/10645578.2019.1668679 Publisher: Routledge _eprint: https://doi.org/10.1080/10645578.2019.1668679

    work page doi:10.1080/10645578.2019.1668679 2019

  62. [62]

    Thomas Serban von Davier, Hayoun Noh, Max Van Kleek, and Nigel Shadbolt

    work page

  63. [63]

    ACM Hum.-Comput

    Looking for Art in a Sea of Content: A Human-Centered Approach to Supporting Creativity on Social Media.Proc. ACM Hum.-Comput. Interact.9, 2 (May 2025), CSCW127:1–CSCW127:25. doi:10.1145/3711025

    work page doi:10.1145/3711025 2025

  64. [64]

    Herman, and Caterina Moruzzi

    Thomas Şerban von Davier, Laura M. Herman, and Caterina Moruzzi. 2024. A Machine Walks into an Exhibit: A Technical Analysis of Art Curation.Arts13, 5 (Oct. 2024), 138. doi:10.3390/arts13050138 Publisher: Multidisciplinary Digital Publishing Institute

    work page doi:10.3390/arts13050138 2024

  65. [65]

    Ron Wakkary and Marek Hatala. 2007. Situated play in a tangible interface and adaptive audio museum guide.Personal Ubiquitous Comput.11, 3 (Feb. 2007), 171–191. doi:10.1007/s00779-006-0101-8

    work page doi:10.1007/s00779-006-0101-8 2007

  66. [66]

    Alexandra Weilenmann, Thomas Hillman, and Beata Jungselius. 2013. Instagram at the museum: communicating the museum experience through social photo sharing. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13). Association for Computing Machinery, New York, NY, USA, 1843–1852. doi:10.1145/2470654.2466243

    work page doi:10.1145/2470654.2466243 2013

  67. [67]

    wikiart.org. 2025. huggan/wikiart·Datasets at Hugging Face. https:// huggingface.co/datasets/huggan/wikiart

    work page 2025

  68. [68]

    Ji Soo Yi, Rachel Melton, John Stasko, and Julie A. Jacko. 2005. Dust & magnet: multivariate information visualization using a magnet metaphor.Information Visualization4, 4 (Oct. 2005), 239–256. doi:10.1057/palgrave.ivs.9500099

    work page doi:10.1057/palgrave.ivs.9500099 2005

  69. [69]

    Yilma and Luis A

    Bereket A. Yilma and Luis A. Leiva. 2023. The Elements of Visual Art Rec- ommendation: Learning Latent Semantic Representations of Paintings. InPro- ceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23). Association for Computing Machinery, New York, NY, USA, 1–17. doi:10.1145/3544548.3581477

    work page doi:10.1145/3544548.3581477 2023

  70. [70]

    Jiajing Zhang, Yongwei Miao, Junsong Zhang, and Jinhui Yu. 2020. Inkthetics: A Comprehensive Computational Model for Aesthetic Evaluation of Chinese Ink Paintings.IEEE Access8 (2020), 225857–225871. doi:10.1109/ACCESS.2020. 3044573

    work page doi:10.1109/access.2020 2020

  71. [71]

    Shichao Zhao, David Kirk, Simon Bowen, and Peter Wright. 2018. Enhancing the Appreciation of Traditional Chinese Painting Using Interactive Technology.Mul- timodal Technologies and Interaction2, 2 (June 2018), 16. doi:10.3390/mti2020016 Publisher: Multidisciplinary Digital Publishing Institute. A Appendix Conference acronym ’XX, June 03–05, 2018, Woodstoc...

    work page doi:10.3390/mti2020016 2018