TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos

ArXi:2605.21443v1 Announce Type: new Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing evaluations, however, treat glitches as static visual anomalies, asking models to detect failures from a single frame. We argue that this framing misses a key distinction: some glitches are spatial and visible in an isolated frame, whereas others are temporal and become evident only through changes across ordered frames.