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Author: 18552

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Automating UI Optimization through Multi-Agentic Reasoning

We present AutoOptimization, a novel multi-objective optimization framework for adapting user interfaces. From a user’s verbal preferences for changing a UI, our framework guides a prioritization-based Pareto frontier search over candidate layouts. It selects suitable objective functions for UI placement while simulta…

Zhipeng Li et al.ETH Zurich

Preference-Guided Prompt Optimization for Text-to-Image Generation

Generative models are increasingly powerful, yet users struggle to guide them through prompts. The generative process is difficult to control and unpredictable, and user instructions may be ambiguous or under-specified. Prior prompt refinement tools heavily rely on human effort, while prompt optimization methods focus…

Zhipeng Li et al.ETH Zurich

SwitchAR: Perceptual Manipulations in Augmented Reality

Perceptual manipulations (PMs) like redirected walking (RDW) are frequently applied in Virtual Reality (VR) to overcome technological limitations. These PMs manipulate the user’s visual perceptions (e.g. through rotational gains), which is currently challenging in Augmented Reality (AR). We propose SwitchAR, a PM for…

Jonas Wombacher et al.Technical University of Darmstadt

Efficient Visual Appearance Optimization by Learning from Prior Preferences

Adjusting visual parameters such as brightness and contrast is common in our everyday experiences. Finding the optimal parameter setting is challenging due to the large search space and the lack of an explicit objective function, leaving users to rely solely on their implicit preferences. Prior work has explored Prefe…

Zhipeng Li et al.ETH Zurich

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Continual Human-in-the-Loop Optimization

Optimal input settings vary across users due to differences in motor abilities and personal preferences, which are typically addressed by manual tuning or calibration. Although human-in-the-loop optimization has the potential to identify optimal settings during use, it is rarely applied due to its long optimization pr…

Yi-Chi Liao et al.ETH Zurich

Modeling the Impact of Visual Stimuli on Redirection Noticeability with Gaze Behavior in Virtual Reality

While users could embody virtual avatars that mirror their physical movements in Virtual Reality, these avatars' motions can be redirected to enable novel interactions. Excessive redirection, however, could break the user's sense of embodiment due to perceptual conflicts between vision and proprioception. While prior…

Zhipeng Li et al.ETH Zurich

SituationAdapt: Contextual UI Optimization in Mixed Reality with Situation Awareness via LLM Reasoning

Mixed Reality is increasingly used in mobile settings beyond controlled home and office spaces. This mobility introduces the need for user interface layouts that adapt to varying contexts. However, existing adaptive systems are designed only for static environments. In this paper, we introduce SituationAdapt, a system…

Zhipeng Li et al.ETH Zurich

Predicting the Noticeability of Dynamic Virtual Elements in Virtual Reality

While Virtual Reality (VR) systems can present virtual elements such as notifications anywhere, designing them so they are not missed by or distracting to users is highly challenging for content creators. To address this challenge, we introduce a novel approach to predict the noticeability of virtual elements. It comp…

Zhipeng Li et al.ETH Zurich

Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention

Despite a rich history of investigating smartphone overuse intervention techniques, AI-based just-in-time adaptive intervention (JITAI) methods for overuse reduction are lacking. We develop Time2Stop, an intelligent, adaptive, and explainable JITAI system that leverages machine learning to identify optimal interventio…

Adiba Orzikulova et al.Korea Advanced Institute of Science and Technology

Reprogrammable Digital Metamaterials for Interactive Devices

We present digital mechanical metamaterials that enable multiple computation loops and reprogrammable logic functions, making a significant step towards passive yet interactive devices. Our materials consist of many cells that transmit signals using an embedded bistable spring. When triggered, the bistable spring disp…

Yu Jiang et al.Tsinghua University

HandAvatar: Embodying Non-Humanoid Virtual Avatars through Hands

We propose HandAvatar to enable users to embody non-humanoid avatars using their hands. HandAvatar leverages the high dexterity and coordination of users' hands to control virtual avatars, enabled through our novel approach for automatically-generated joint-to-joint mappings. We contribute an observation study to unde…

Yu Jiang et al.Tsinghua University

Color-to-Depth Mappings as Depth Cues in Virtual Reality

Despite significant improvements to Virtual Reality (VR) technologies, most VR displays are fixed focus and depth perception is still a key issue that limits the user experience and the interaction performance. To supplement humans' inherent depth cues (e.g., retinal blur, motion parallax), we investigate users' perce…

Zhipeng Li et al.ETH Zurich

Accurate and Low-Latency Sensing of Touch Contact on Any Surface with Finger-Worn IMU Sensor

Head-mounted Mixed Reality (MR) systems enable touch interaction on any physical surface. However, optical methods (i.e., with cameras on the headset) have difficulty in determining the touch contact accurately. We show that a finger ring with Inertial Measurement Unit (IMU) can substantially improve the accuracy of c…

Yizheng Gu et al.Tsinghua University

Paper Title	Authors	Research Topics	Paper Database	Year
emoji_events Automating UI Optimization through Multi-Agentic Reasoning We present AutoOptimization, a novel multi-objective optimization framework for adapting user interfaces. From a user’s verbal preferences for changing a UI, our framework guides a prioritization-based Pareto frontier search over candidate layouts. It selects suitable objective functions for UI placement while simulta…	ZL Zhipeng Li et al.ETH Zurich
Preference-Guided Prompt Optimization for Text-to-Image Generation Generative models are increasingly powerful, yet users struggle to guide them through prompts. The generative process is difficult to control and unpredictable, and user instructions may be ambiguous or under-specified. Prior prompt refinement tools heavily rely on human effort, while prompt optimization methods focus…	ZL Zhipeng Li et al.ETH Zurich
SwitchAR: Perceptual Manipulations in Augmented Reality Perceptual manipulations (PMs) like redirected walking (RDW) are frequently applied in Virtual Reality (VR) to overcome technological limitations. These PMs manipulate the user’s visual perceptions (e.g. through rotational gains), which is currently challenging in Augmented Reality (AR). We propose SwitchAR, a PM for…	JW Jonas Wombacher et al.Technical University of Darmstadt
Efficient Visual Appearance Optimization by Learning from Prior Preferences Adjusting visual parameters such as brightness and contrast is common in our everyday experiences. Finding the optimal parameter setting is challenging due to the large search space and the lack of an explicit objective function, leaving users to rely solely on their implicit preferences. Prior work has explored Prefe…	ZL Zhipeng Li et al.ETH Zurich
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
emoji_events Continual Human-in-the-Loop Optimization Optimal input settings vary across users due to differences in motor abilities and personal preferences, which are typically addressed by manual tuning or calibration. Although human-in-the-loop optimization has the potential to identify optimal settings during use, it is rarely applied due to its long optimization pr…	YL Yi-Chi Liao et al.ETH Zurich
Modeling the Impact of Visual Stimuli on Redirection Noticeability with Gaze Behavior in Virtual Reality While users could embody virtual avatars that mirror their physical movements in Virtual Reality, these avatars' motions can be redirected to enable novel interactions. Excessive redirection, however, could break the user's sense of embodiment due to perceptual conflicts between vision and proprioception. While prior…	ZL Zhipeng Li et al.ETH Zurich
SituationAdapt: Contextual UI Optimization in Mixed Reality with Situation Awareness via LLM Reasoning Mixed Reality is increasingly used in mobile settings beyond controlled home and office spaces. This mobility introduces the need for user interface layouts that adapt to varying contexts. However, existing adaptive systems are designed only for static environments. In this paper, we introduce SituationAdapt, a system…	ZL Zhipeng Li et al.ETH Zurich
Predicting the Noticeability of Dynamic Virtual Elements in Virtual Reality While Virtual Reality (VR) systems can present virtual elements such as notifications anywhere, designing them so they are not missed by or distracting to users is highly challenging for content creators. To address this challenge, we introduce a novel approach to predict the noticeability of virtual elements. It comp…	ZL Zhipeng Li et al.ETH Zurich
Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention Despite a rich history of investigating smartphone overuse intervention techniques, AI-based just-in-time adaptive intervention (JITAI) methods for overuse reduction are lacking. We develop Time2Stop, an intelligent, adaptive, and explainable JITAI system that leverages machine learning to identify optimal interventio…	AO Adiba Orzikulova et al.Korea Advanced Institute of Science and Technology
Reprogrammable Digital Metamaterials for Interactive Devices We present digital mechanical metamaterials that enable multiple computation loops and reprogrammable logic functions, making a significant step towards passive yet interactive devices. Our materials consist of many cells that transmit signals using an embedded bistable spring. When triggered, the bistable spring disp…	YJ Yu Jiang et al.Tsinghua University
HandAvatar: Embodying Non-Humanoid Virtual Avatars through Hands We propose HandAvatar to enable users to embody non-humanoid avatars using their hands. HandAvatar leverages the high dexterity and coordination of users' hands to control virtual avatars, enabled through our novel approach for automatically-generated joint-to-joint mappings. We contribute an observation study to unde…	YJ Yu Jiang et al.Tsinghua University
Color-to-Depth Mappings as Depth Cues in Virtual Reality Despite significant improvements to Virtual Reality (VR) technologies, most VR displays are fixed focus and depth perception is still a key issue that limits the user experience and the interaction performance. To supplement humans' inherent depth cues (e.g., retinal blur, motion parallax), we investigate users' perce…	ZL Zhipeng Li et al.ETH Zurich
Accurate and Low-Latency Sensing of Touch Contact on Any Surface with Finger-Worn IMU Sensor Head-mounted Mixed Reality (MR) systems enable touch interaction on any physical surface. However, optical methods (i.e., with cameras on the headset) have difficulty in determining the touch contact accurately. We show that a finger ring with Inertial Measurement Unit (IMU) can substantially improve the accuracy of c…	YG Yizheng Gu et al.Tsinghua University