AUIT – the Adaptive User Interfaces Toolkit for Designing XR Applications
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Adaptive user interfaces can improve experiences in Extended Reality (XR) applications by adapting interface elements according to the user’s context. Although extensive work explores different adaptation policies, XR creators often struggle with their implementation, which involves laborious manual scripting. The few available tools are underdeveloped for realistic XR settings where it is often necessary to consider conflicting aspects that affect an adaptation. We fill this gap by presenting AUIT, a toolkit that facilitates the design of optimization-based adaptation policies. AUIT allows creators to flexibly combine policies that address common objectives in XR applications, such as element reachability, visibility, and consistency. Instead of using rules or scripts, specifying adaptation policies via adaptation objectives simplifies the design process and enables creative exploration of adaptations. After creators decide which adaptation objectives to use, a multi-objective solver finds appropriate adaptations in real-time. A study showed that AUIT allowed creators of XR applications to quickly and easily create high-quality adaptations.
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System adaptability can be beneficial to oversight if oversight persons can adapt the system's processes or its interface.
“It can be beneficial to oversight if oversight persons can adapt the system's processes or its interface [25, 69].”
From On the Quest for Effectiveness in Human Oversight: Interdisciplinary Perspectives (2024) · cites this paper as [25]
The D4 section says creators can customize when and why an XR interface adapts, and the Discussion reports benefits for creating adaptive interfaces. The paper identifies those creators as application developers or designers, not oversight personnel; it does not establish a benefit to oversight or address adapting system processes more broadly. Page numbers are unavailable in our copy. (LLM, conf=0.78)
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VoxAR: Adaptive Visualization of Volume Rendered Objects in Optical See-Through Augmented Reality
Boorboor, S., Castellana, M. S., Kim, Y., Chen, Z.-T., Beyer, J., Pfister, H., & Kaufman, A. E. (2023) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2023.3340770 · Cited by 9
“Evangelista et al. have developed AUIT [3] that allows users to customize the placement process: hook into existing abstracted data sources, write their own objectives, determine solvers and when to trigger them, and how to transition between changing states.”
BackgroundMethodInfluentialUbiSurface: A Robotic Touch Surface for Supporting Mid-air Planar Interactions in Room-Scale VR
Gomi, R., Takashima, K., Onishi, Y., Fujita, K., & Kitamura, Y. (2023) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3626479 · Cited by 9
“For example, in recent years researchers have proposed toolkits to automatically design optimally personalized VR workspaces for individual users[19, 20].”
BackgroundPei, Y., Huang, R., Zha, M., Wang, G., Wang, P., Kang, Q., Yang, Y., & Shen, H. T. (2025) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3746059.3747674 · Cited by 4 · see citing works
Preference-Guided Multi-Objective UI Adaptation
Song, Y., Gebhardt, C., Liao, Y.-C., & Holz, C. (2025) · ACM Symposium on User Interface Software and Technology · doi:10.1145/3746059.3747645 · Cited by 8
Introduction to Human-Computer Interaction
Hornbæk, K., Kristensson, P. O., & Oulasvirta, A. (2025) · doi:10.1093/oso/9780192864543.001.0001 · Cited by 8 · see citing works
Self-citationA Framework for Computational Design and Adaptation of Extended Reality User Interfaces
Todi, K., & Jonker, T. R. (2023) · arXiv.org · doi:10.48550/arxiv.2309.04025 · Cited by 8
Zhou, X., Lee, B., Ortega, F., Batmaz, A. U., & Yang, Y.-L. (2024) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3698147 · Cited by 7 · see citing works
Wang, X.-Y., Zhang, W.-Z., Sandor, C., & Fu, H. (2024) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3466554 · Cited by 7
“From the perspective of User Interface (UI), researchers also explore the placement of UI components in AR and VR regarding user’s social and physical comfortableness in public transit [39], the UI elements’ relations with each other and the physical environment [40], and users’ cognitive load [54].”
InfluentialPlümer, J. H., & Tatzgern, M. (2023) · International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar59233.2023.00096 · Cited by 7 · see citing works
“…work explored the use of simulation for prototyping novel interfaces and products [5,31], or demonstrated general feasibility of novel solutions [25,43], the question of ecological validity remains, i.e., to what degree the results gathered in XR simulations are transferrable to real-world…”
BackgroundEfficient Human-in-the-Loop Optimization via Priors Learned from User Models
Liao, Y.-C., Belo, J. M. E., Moon, H.-S., Steimle, J., & Feit, A. (2025) · International Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791976 · Cited by 6
“Examples include menu optimization [4, 79], keyboard layout design [18, 27], and user interface layout adaptation in AR/VR environments [17, 48], and more.”
Self-citationPerceived Text Relevance Estimation Using Scanpaths and GNNs
Selim, A. M., Bhatti, O. S., Barz, M., & Sonntag, D. (2024) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3678957.3685736 · Cited by 7 · see citing works
Gottsacker, M., Chen, M.-Y., Saffo, D., Lu, F.-Y., & MacIntyre, B. (2023) · 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct60411.2023.00046 · Cited by 6
“Recent research has demonstrated the potential of adaptive content placement for productivity work [10,11].”
BackgroundLai, C.-J., Sousa, M., Zhang, T., Sidenmark, L., & Grossman, T. (2025) · ACM Symposium on User Interface Software and Technology · doi:10.1145/3746059.3747790 · Cited by 5 · see citing works
Minton, A. G., Zhu, H. Y., Chen, H.-T., Wang, Y.-K., Zhuang, Z., Notaro, G., Galvan, R., Allen, J., Ziegler, M. D., & Lin, C.-T. (2025) · International Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713402 · Cited by 5 · see citing works
Knowledge-based approach to adaptive XR interface design for non-programmers
Maik, M., Flotyński, J., & Walczak, K. (2024) · The Visual Computer · doi:10.1007/s00371-024-03472-6 · Cited by 5
“Theemergence of no-code platforms in XR content creation has significantly lowered barriers for non-technical creators in areas such as 3D graphics and physics simulation [4].”
Raianova, A., & Lee, M. (2025) · 2025 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct68609.2025.00046 · Cited by 4 · see citing works
AdjustAR: AI-Driven In-Situ Adjustment of Site-Specific Augmented Reality Content
Numan, N., Brummelen, J. V., Lu, Z., & Steed, A. (2025) · UIST Adjunct · doi:10.1145/3746058.3758362 · Cited by 4 · see citing works
An Exploratory Study on AI-driven Visualisation Techniques on Decision Making in Extended Reality
Dong, Z., Han, B., Zhang, J., Wen, R., Ens, B., Clark, A. J., & Piumsomboon, T. (2024) · Australasian Computer-Human Interaction Conference · doi:10.1145/3726986.3727036 · Cited by 4 · see citing works
Brushing and Linking for Situated Analytics
Quijano-Chavez, C., Doerr, N., Lee, B., Schmalstieg, D., & Sedlmair, M. (2024) · 2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · doi:10.1109/vrw62533.2024.00116 · Cited by 4
Automating UI Optimization through Multi-Agentic Reasoning
Li, Z.-P., Gebhardt, C., Liao, Y.-C., & Holz, C. (2026) · International Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791444 · Cited by 3 · see citing works
Enhancing Spatial Understanding in Mixed-Reality Presentations
Vo, N.-D., Thai, V.-V., Hoai, N. V., Huynh, V.-T., Tang, A., & Le, K.-D. (2025) · ACM Symposium on Virtual Reality Software and Technology (VRST) · doi:10.1145/3756884.3766024 · Cited by 1 · see citing works
MorphGUI: Real-time GUIs customization with large language models
Calò, T., Sillano, A., & Russis, L. D. (2025) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2025.103695 · Cited by 3
Holistic quantified-self for context-aware wearable augmented reality
Song, E., Ha, T., Park, J., Lee, H., & Woo, W. (2025) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2025.103568 · Cited by 3 · see citing works
Zhu, F., Qian, X., Kalmar, D., Tayarani, M., Gonzalez, E. J., González-Franco, M., Kim, D., & Du, R.-F. (2025) · IEEE Conference on Virtual Reality and 3D User Interfaces · doi:10.1109/vr59515.2025.00099 · Cited by 3 · see citing works
“With advancements in the perception capabilities of XR devices, researchers have leveraged these improvements to dynamically adapt content—such as spatial user interfaces—based on environmental context [40, 5, 31, 35].”
GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI Design
Caetano, A., Luo, Y., Sharma, A., & Sra, M. (2025) · ACM Symposium on User Interface Software and Technology · doi:10.1145/3746059.3747744 · Cited by 3 · see citing works
“AUIT [16] is an adaptive XR interface toolkit that enables adaptions through multi-object optimization, such as visibility and reachability, while allowing cus-tomizations.”
Lu, F., Pavanatto, L., Davari, S., Zhang, L., Lisle, L., & Bowman, D. A. (2024) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2024.3493115 · Cited by 3 · see citing works
“Beloetal.deployedaadaptive UItoolkitforoptimizingtheplacementof3DUIsaccording toasetofobjectives[28].”
Adaptive Content Placement in Mixed Reality Through Empirical User Behavioral Patterns
Lu, F.-Y., Chen, M.-Y., Hsu, H., Deshpande, P., Wang, C.-Y., & MacIntyre, B. (2024) · 2024 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct64951.2024.00049 · Cited by 3
Opportunities and Challenges of Hybrid User Interfaces for Optimization of Mixed Reality Interfaces
Zaky, A., Zagermann, J., Reiterer, H., & Feuchtner, T. M. (2023) · 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct60411.2023.00050 · Cited by 3 · see citing works
“The reachable interaction space can thereby be represented as a half-sphere [3], and reachability can be accommodated for example with cylindrical layouts for user interface elements [5].”
BackgroundMethodInfluentialIntersecting Realms: Examining the Convergence of Vision and AI in Extended Reality Graphics
Alhakamy, A. (2025) · IEEE Access · doi:10.1109/access.2025.3599337 · Cited by 4 · see citing works
“(2) Adaptive Interactions and Personalization and examining the techniques that can be implemented to develop AI-powered real-time adaptive learning environments in XR, which modify difficulty levels or content in response to user performance [23].”
Open-Source Toolkits for Experiments in Virtual Reality: A Scoping Review
Thomsen, L., & Krueger, R. (2026) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2026.3679886 · Cited by 2 · see citing works
“Specializing in a different area, the Adaptive User Interfaces Toolkit (AUIT) [20] facilitates the design of optimization-based adaptive user interfaces in Unity.”
A decision-theoretic representation of assistive interfaces
Gori, J., Nioche, A., Johns, C. A., & Oulasvirta, A. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791819
Self-citationSimulating Human Audiovisual Search Behavior
Cho, H., Luo, X.-J., Lee, B., Lindlbauer, D., & Oulasvirta, A. (2026) · International Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790614 · Cited by 2
Self-citationDuoZone: A User-Centric, LLM-Guided Mixed-Initiative XR Window Management System
Qian, J., Wang, G., Li, X.-Y., Wen, Y.-G., Wu, G.-D., Quispe, S., Yang, F., & Silva, C. (2025) · arXiv.org · doi:10.48550/arxiv.2511.15676 · Cited by 2
Koh, Y., Bailly, G., & Avellino, I. (2025) · Interaction Homme-Machine · doi:10.1145/3765712.3765733 · Cited by 2 · see citing works
Lee, S.-C., Chang, Y., Wang, C.-H., Chen, B.-Y., & Chan, L.-W. (2025) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3743716 · Cited by 2
“Additionally, Belo et al. [6] introduced an optimization framework called AUIT, which enables creators to experiment with adaptation goals derived from custom usability factors for UI placements.”
InfluentialCheng, Y., Carden, A., Cho, H., Fidalgo, C. G., Wieland, J., & Lindlbauer, D. (2025) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2025.3592962 · Cited by 2 · see citing works
“Sev-eralpriorworkshaveexploredoptimization-basedapproachesto adaptinginterfacesbasedonvariouscontextualfactors,suchas environmentsemantics[18],userplacementpreferences[67], andusabilityrequirements[30].”
Rajaram, S. (2024) · ACM Symposium on User Interface Software and Technology · doi:10.1145/3672539.3686708 · Cited by 2 · see citing works
Designing Situated Dashboards: Challenges and Opportunities
Sayara, A., Lee, B., Quijano-Chavez, C., & Sedlmair, M. (2023) · 2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) · doi:10.1109/ismar-adjunct60411.2023.00028 · Cited by 2
“It is safe to assume that dashboards could be moved manually, but automatic solutions may also be employed (e.g., [16]).”
User Preferences for UI Anchoring in MR: Effects of Task Mobility and Interface Properties
Belo, J., Elahimanesh, S., & Feit, A. (2026) · doi:10.48550/arxiv.2608.28064 · Cited by 1
“Beyond manual control, automatically adjusting the UI position at runtime within a specific frame of reference has also been explored using constraint-driven [3] methods and optimization approaches [33, 18].”
Self-citationSpatial Context Switches During Knowledge Tasks in Extended Reality
Büschel, W., Biener, V., & Schmalstieg, D. (2026) · International Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791416 · Cited by 1 · see citing works
“Evangelista et al. [17] presented a toolkit for combining different adaptation objectives.”
SPAR: Automated Static Placement of Virtual Content via Ergonomic‐Aware Multi‐Objective Optimization
Wang, Y.-W., & Zhao, X. (2026) · Computer graphics forum (Print) · doi:10.1111/cgf.70429 · Cited by 1 · see citing works
Balancing Flow and Collaboration: Exploring Visual Noise Cancellation in Mixed Reality Workspace
Chen, X., Zhou, X., Jian, X.-F., Zhou, L., Zhang, L.-P., Sun, H.-F., Qi, Q., Wang, J., & Wang, J.-Y. (2026) · International Conference on Intelligent User Interfaces · doi:10.1145/3742413.3789114 · Cited by 1 · see citing works
“Adaptive User Interfaces (AUI) can enhance user experience by adjusting their elements and layout based on the user’s requirements or context [16, 20].”
The Invisible Hand of the Context: Authoring of Context-Aware Mixed Reality Labels
Baader, J., Ellenberg, M. O., & Satkowski, M. (2025) · Message Understanding Conference · doi:10.1145/3743049.3748552 · Cited by 1
“Adaptive MR interfaces address the challenges of when , where , and how to present information in response to changing user and environmental conditions [11, 17, 32].”
XARP: A Human-First and Agent-Ready Extended Reality Toolkit in Python
Caetano, A., Kumaran, R., Jou, K., Höllerer, T., & Sra, M. (2025) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3816762 · Cited by 1
Lipkowitz, G. (2024) · ACM Symposium on User Interface Software and Technology · doi:10.1145/3672539.3686780 · Cited by 1
Paradiegetic user interfaces: balancing immersion and information clarity in virtual reality
Yu, H.-J., Kang, S., Lee, S., & Park, J. (2026) · Behaviour & Information Technology · doi:10.1080/0144929x.2026.2749501
SplatXR: A Toolkit for Multi-Layered Extended Reality via On-Headset 3D Gaussian Splatting
Vachha, C., Kari, M., & Abtahi, P. (2026) · doi:10.1145/3830398.3830681
Say It or Grab It? Conversational Control of UI Adaptations in Mixed Reality
Elahimanesh, S., Belo, J., Jeknić, I., Koller, A., & Feit, A. (2026) · doi:10.48550/arxiv.2610.24640
Self-citationRhee, J., Lee, G., Jung, Y.-M., Dogan, M. D., Moon, K., & Bianchi, A. (2026) · doi:10.1145/3859325
“Those comparisons weigh alternatives a designer freely explores, and condition-indexed previews adapt the same aid to a different question: whether one design stays legible and usable under each situation it will meet—a concern readability research in AR documents across lighting, background, and…”
Tromp, J. G., & van der Minne, S. M. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2739088
MultiVerse: A Creator-Centered Approach to Steering Context-Adaptive Lyrics
Wang, A., Donahue, C., & Lindlbauer, D. (2026) · doi:10.1145/3830398.3830530
“While substantial prior work focuses on adapting interface elements without altering the underlying content [9, 12, 18, 31], context-awareness is applied to modify the content itself, shaping storytelling media across modalities such as VR [72], film [32], video captions [35], books [28],…”
Generative Proxy: Synthesizing Proxy-Based Interfaces for Real-World Interaction Across AR Glasses
Liu, X. C., Chastek, W., Gonzalez, E. J., González-Franco, M., & Chen, Z.-T. (2026) · doi:10.1145/3830398.3830482
“Authoring tools such as CAPturAR [61], AUIT [11], and ScalAR [49] further lower the barrier to building adaptive AR applications.”
Visualizing Placement Proposals for Window Arrangement in Mixed Reality: A Comparative User Study
Zaky, A., & Feuchtner, T. M. (2026) · Proceedings of the 2026 ACM Symposium on Spatial User Interaction · doi:10.1145/3822518.3830056
“…sample comprised primarily young, tech-savvy university students with moderate-to-high prior VR/AR exposure and high familiarity with 2D window management; the strong preference for Manual Positioning may partly reflect this familiarity (legacy-bias) and may not generalize to the wider population.”
InfluentialUI Placement as a Critical Design Factor for Augmented Reality During Locomotion
Manakhov, P., & Gellersen, H. (2026) · arXiv.org · doi:10.48550/arxiv.2604.06102
“…tag-along UIs that remain stationary relative to the world within a defined threshold around the user but are pulled along once that threshold is exceeded [11] (Figure 2a), or UIs that travel with the user while dynamically adjusting their position to avoid overlapping with world geometry [1].”
Designing Fatigue-Aware VR Interfaces via Biomechanical Models
Voleti, H., & Poullis, C. (2026) · Engineering Interactive Computing System · doi:10.1145/3807968.3816097
Dong, Z., Han, B., Zhang, J., Ens, B., Clark, A. J., & Piumsomboon, T. (2025) · International Conference on Advancements in Computational Sciences · doi:10.1145/3789418.3789450
Thakur, R. (2025) · World Journal of Advanced Research and Reviews · doi:10.30574/wjarr.2025.26.2.1869
“Studies demonstrate that users strongly prefer interfaces that maintain consistency in element positioning while adapting presentation characteristics based on context, as this approach preserves spatial memory while enhancing readability across usage scenarios [7].”
InfluentialAkça, E., Tanrıöver, Ö. Ö., & Yılmaz, A. (2025) · IEEE Access · doi:10.1109/access.2025.3596286
“Furthermore, there is a rising need for practical and effective design methods to cope with UIs where variable contents are to be presented for advancing display technologies [1], [2].”
- Authors
- Evangelista Belo, J. M., Lystbæk, M. N., Feit, A. M., Pfeuffer, K., Kán, P., Oulasvirta, A., & Grønbæk, K.
- Affiliations
- Department of Computer Science, Aarhus University, Denmark
- Aarhus University (DK)
- Saarland University (DE)
- TU Wien (AT)
- Aalto University (FI)
- Venue
- Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology
- Publisher
- ACM
- Published
- 2022-10-28
- Pages
- 1-16
- OpenAlex
- W4307475996
- Cited by
- 117
- References
- 56
- Citations by year
- 2026: 10 · 2025: 74 · 2024: 21 · 2023: 12
- FWCI
- 21.40
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- ACM Symposium on User Interface Software and Technology (UIST) (publishedVersion, cc-by)
- Aaltodoc (Aalto University) (submittedVersion, cc-by)
- Funders
- Innovation Fund Denmark (6151-00006B)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Keywords
- adaptive user interfaces, extended reality, adaptation policy, multi-objective optimization, real-time adaptation, visibility, consistency, user context
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