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Rohan Paul· @rohanpaul_ai · X· · 原发布时间 AI 评分54

Google、UCLA 与 CMU 研究者推出 XR 编程智能体基准 GenXR-Bench

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研究者构建了覆盖功能开发、修复错误和完整应用构建的 112 项任务,并模拟手部与房间输入来测试 XR 应用。引述的研究结果显示,Claude Opus 5 的完成率最高,为 50.9%;在 SDK 功能任务上,没有模型超过 29.2%。失败运行中,64.4% 出现坐标系错误。

原帖引用 · 原文

@rohanpaul_ai

– https://t.co/gYptG6nGX9

Title: "GenXR-Bench: Benchmarking Coding Agents for Interactive XR Development"

回复Rohan Paul@rohanpaul_ai
New Google + UCLA + CMU paper finds that AI coding tools often fail to build virtual and mixed reality apps because they lose track of where things are in 3D space. Claude Opus 5 led at 50.9%, and no model topped 29.2% on SDK feature tasks. Coordinate-frame mistakes appeared in 64.4% of failed runs, and startup race conditions in 44.9%. XR apps run in 3D space and react to head motion, hands, and room sensing. Normal coding benchmarks use unit tests or browser clicks, which cannot check whether a virtual button follows your palm. They built GenXR-Bench, 112 expert-written tasks covering XR feature work, bug fixes, and full app builds. Its tests simulate hands and rooms, and matched blinded XR experts using real headsets 96.5% of the time. If you use agents for XR apps, test the result with simulated hand and room input, since agent-written unit tests often miss runtime bugs.
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来源:Rohan Paul · x.com

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