RefGlitch-Bench: A Benchmark for Reference-based Gameplay Glitch Detection with Vision-Language Models
Visual glitches in video games degrade player experience and perceived quality, yet manual quality assurance cannot keep pace with the growing test surface of modern game development. Prior automation efforts, particularly those using vision-language models (VLMs), largely operate on isolated frames without sufficient context to judge whether a glitch is present. We introduce RefGlitch-Bench, a benchmark for reference-based video game glitch detection with VLMs. The key idea is to formulate glitch detection as an explicit within-video comparison problem: given a test frame, a reference frame provides a visual baseline that helps the model distinguish true glitches from benign visual varia...
| Authors | Yakun Yu, Ashley Wiens, Adrián Barahona-Ríos et al. |
|---|---|
| Primary category | cs.CV |
| Published | 13 April 2026 |
| Last updated at source | 15 September 2026 |
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