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

Google、UCLA 与 CMU 研究发现 AI 编程工具难以完成 XR 应用任务

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研究团队构建了含 112 道专家编写任务的 GenXR-Bench,用模拟手部与房间输入测试 XR 功能开发、修复和完整应用构建。Claude Opus 5 的总体成绩领先,为 50.9%;在 SDK 功能任务上,没有模型超过 29.2%,失败运行中常见三维坐标系错误。

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@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.

来源:Rohan Paul · x.com

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