GenXR-Bench: Benchmarking Coding Agents for Interactive XR Development
We introduce GenXR-Bench, the first benchmark for the end-to-end evaluation of coding agents in XR software development.
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Key points
- Coding agents are rapidly advancing from single-file generation to long-horizon repository-scale engineering, yet the evaluation of their capabilities to author interactive extended reality (XR) applications remains an open challenge.
- Unlike traditional software, XR applications operate within dynamic 3D physical environments where runtime robustness depends jointly on continuous user motion, spatial input, and environmental sensing.
- Failure analysis identifies recurring misunderstandings in asynchronous sensor lifecycles, physical grounding, and embodied interaction semantics.
- GenXR-Bench establishes a reproducible testbed for evaluating coding agents in the interactive and physically situated conditions of spatial computing.
Sources (1)
- [1]GenXR-Bench: Benchmarking Coding Agents for Interactive XR DevelopmentarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 21, 12:28 AM
We introduce GenXR-Bench, the first benchmark for the end-to-end evaluation of coding agents in XR software development.
Coding agents are rapidly advancing from single-file generation to long-horizon repository-scale engineering, yet the evaluation of their capabilities to author interactive extended reality (XR) applications remains an open challenge.
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