LLMR: Real-time Prompting of Interactive Worlds using Large Language Models
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Abstract (arXiv)
We present Large Language Model for Mixed Reality (LLMR), a framework for the real-time creation and modification of interactive Mixed Reality experiences using LLMs. LLMR leverages novel strategies to tackle difficult cases where ideal training data is scarce, or where the design goal requires the synthesis of internal dynamics, intuitive analysis, or advanced interactivity. Our framework relies on text interaction and the Unity game engine. By incorporating techniques for scene understanding, task planning, self-debugging, and memory management, LLMR outperforms the standard GPT-4 by 4x in average error rate. We demonstrate LLMR's cross-platform interoperability with several example worlds, and evaluate it on a variety of creation and modification tasks to show that it can produce and edit diverse objects, tools, and scenes. Finally, we conducted a usability study (N=11) with a diverse set that revealed participants had positive experiences with the system and would use it again.
Key facts. Cited by 39 papers in the map (data through 7 Oct 2026). Builds on 38 of its 116 references that are in the map. First posted on arXiv 21 Sep 2023.
Builds on
38 of 116 references.
References · 38
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- 2021A Survey on Synchronous Augmented, Virtual and Mixed Reality Remote Collaboration Systemscited by 5
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Citing papers per year: 2023: 1; 2024: 14; 2025: 17; 2026: 7.
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- 2026Memento: Towards Proactive Visualization of Everyday Memories with Personal Wearable AR Assistant24 Jan 2026
- 2026When Generative AI Meets Extended Reality: Enabling Scalable and Natural Interactions13 Jan 2026
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- 2025Empowering Children to Create AI-Enabled Augmented Reality Experiences11 Aug 2025
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