DuoZone: A User-Centric, LLM-Guided Mixed-Initiative XR Window Management System
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908665688096768 |
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| author | Qian, Jing Wang, George X. Li, Xiangyu Wen, Yunge Wu, Guande Quispe, Sonia Castelo Yang, Fumeng Silva, Claudio |
| author_facet | Qian, Jing Wang, George X. Li, Xiangyu Wen, Yunge Wu, Guande Quispe, Sonia Castelo Yang, Fumeng Silva, Claudio |
| contents | Mixed reality (XR) environments offer vast spatial possibilities, but current window management systems require users to manually place, resize, and organize multiple applications across large 3D spaces. This creates cognitive and interaction burdens that limit productivity. We introduce DuoZone, a mixed-initiative XR window management system that combines user-defined spatial layouts with LLM-guided automation. DuoZone separates window management into two complementary zones. The Recommendation Zone enables fast setup by providing spatial layout templates and automatically recommending relevant applications based on user tasks and high-level goals expressed through voice or text. The Arrangement Zone supports precise refinement through direct manipulation, allowing users to adjust windows using natural spatial actions such as dragging, resizing, and snapping. Through this dual-zone approach, DuoZone promotes efficient organization while reducing user cognitive load. We conducted a user study comparing DuoZone with a baseline manual XR window manager. Results show that DuoZone improves task completion speed, reduces mental effort, and increases sense of control when working with multiple applications in XR. We discuss design implications for future mixed-initiative systems and outline opportunities for integrating adaptive, goal-aware intelligence into spatial computing workflows. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_15676 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DuoZone: A User-Centric, LLM-Guided Mixed-Initiative XR Window Management System Qian, Jing Wang, George X. Li, Xiangyu Wen, Yunge Wu, Guande Quispe, Sonia Castelo Yang, Fumeng Silva, Claudio Human-Computer Interaction Mixed reality (XR) environments offer vast spatial possibilities, but current window management systems require users to manually place, resize, and organize multiple applications across large 3D spaces. This creates cognitive and interaction burdens that limit productivity. We introduce DuoZone, a mixed-initiative XR window management system that combines user-defined spatial layouts with LLM-guided automation. DuoZone separates window management into two complementary zones. The Recommendation Zone enables fast setup by providing spatial layout templates and automatically recommending relevant applications based on user tasks and high-level goals expressed through voice or text. The Arrangement Zone supports precise refinement through direct manipulation, allowing users to adjust windows using natural spatial actions such as dragging, resizing, and snapping. Through this dual-zone approach, DuoZone promotes efficient organization while reducing user cognitive load. We conducted a user study comparing DuoZone with a baseline manual XR window manager. Results show that DuoZone improves task completion speed, reduces mental effort, and increases sense of control when working with multiple applications in XR. We discuss design implications for future mixed-initiative systems and outline opportunities for integrating adaptive, goal-aware intelligence into spatial computing workflows. |
| title | DuoZone: A User-Centric, LLM-Guided Mixed-Initiative XR Window Management System |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2511.15676 |