7 papers
Automating UI Optimization through Multi-Agentic Reasoning
Zhipeng Li, Christoph Gebhardt, Yi-Chi Liao +1
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…
Preference-Guided Prompt Optimization for Text-to-Image Generation
Zhipeng Li, Yi-Chi Liao, Christian Holz
Generative models are increasingly powerful, yet users struggle to guide them through prompts. The generative process is difficult to control and unpredictable, and user instructio…
Group Inertial Poser: Multi-Person Pose and Global Translation from Sparse Inertial Sensors and Ultra-Wideband Ranging
Ying Xue, Jiaxi Jiang, Rayan Armani +3
Tracking human full-body motion using sparse wearable inertial measurement units (IMUs) overcomes the limitations of occlusion and instrumentation of the environment inherent in vi…
Preference-Guided Multi-Objective UI Adaptation
Yao Song, Christoph Gebhardt, Yi-Chi Liao +1
3D Mixed Reality interfaces have nearly unlimited space for layout placement, making automatic UI adaptation crucial for enhancing the user experience. Such adaptation is often for…
Efficient Visual Appearance Optimization by Learning from Prior Preferences
Zhipeng Li, Yi-Chi Liao, Christian Holz
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 spac…
Continual Human-in-the-Loop Optimization
Yi-Chi Liao, Paul Streli, Zhipeng Li +2
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 hum…