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Rohan Paul· @rohanpaul_ai · X· · Original publication time AI score54

Google, UCLA and CMU study finds AI coding tools struggle with XR app tasksMachine translation

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The researchers built GenXR-Bench with 112 expert-written tasks covering XR features, bug fixes and full app builds, tested with simulated hand and room input. Claude Opus 5 led overall at 50.9%, but no model exceeded 29.2% on SDK feature tasks; coordinate-frame errors were common in failed runs.

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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.

Source: Rohan Paul · x.com

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