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Computer Science > Human-Computer Interaction

arXiv:2603.24591 (cs)
[Submitted on 25 Mar 2026 (v1), last revised 3 Apr 2026 (this version, v2)]

Title:Vibe Coding XR: Accelerating AI + XR Prototyping with XR Blocks and Gemini

Authors:Ruofei Du, Benjamin Hersh, David Li, Nels Numan, Xun Qian, Yanhe Chen, Zhongyi Zhou, Xingyue Chen, Jiahao Ren, Robert Timothy Bettridge, Xiang 'Anthony' Chen, Faraz Faruqi, Steve Toh, David Kim
View a PDF of the paper titled Vibe Coding XR: Accelerating AI + XR Prototyping with XR Blocks and Gemini, by Ruofei Du and 13 other authors
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Abstract:While large language models (LLMs) have accelerated 2D software development through intent-driven "vibe coding", prototyping intelligent Extended Reality (XR) experiences remains a major challenge. The fundamental barrier is not just the steep learning curve for human creators, but that low-level sensor APIs and complex game engine hierarchies are ill-suited for LLM reasoning, routinely exceeding context windows and inducing syntax hallucinations. To bridge this gap, we contribute XR Blocks, an open-source, LLM-native WebXR framework. Unlike traditional engines, XR Blocks introduces a semantic "Reality Model" that aligns spatial computing primitives (users, physical environments, and agents) with natural language, providing a robust, concise vocabulary optimized for generative AI. Building upon this foundation, we present Vibe Coding XR, an end-to-end prototyping workflow that leverages LLMs to translate high-level prompts (e.g., "create a dandelion that reacts to my hand") directly into functional, physics-aware mixed-reality applications. To minimize the friction of on-device testing, the workflow introduces a seamless desktop "simulated reality" to headset deployment loop. Finally, we introduce VCXR60, a pilot dataset of 60 XR prompts paired with an automated evaluation pipeline. Our technical evaluation demonstrates high one-shot execution success, enabling practitioners to bypass lowlevel hurdles and rapidly move from "idea to reality". Code and live demos are available at this https URL and this http URL.
Subjects: Human-Computer Interaction (cs.HC)
Cite as: arXiv:2603.24591 [cs.HC]
  (or arXiv:2603.24591v2 [cs.HC] for this version)
  https://doi.org/10.48550/arXiv.2603.24591
arXiv-issued DOI via DataCite

Submission history

From: Ruofei Du [view email]
[v1] Wed, 25 Mar 2026 17:58:56 UTC (3,833 KB)
[v2] Fri, 3 Apr 2026 16:34:38 UTC (3,846 KB)
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