27 citations · 89 across the 22 of their papers we have counts for
8 papers · 1 filter
TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos
Yakun Yu, Ashley Wiens, Adrián Barahona-Ríos +4
Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing evaluations, however, treat glit…
RefGlitch-Bench: A Benchmark for Reference-based Gameplay Glitch Detection with Vision-Language Models
Yakun Yu, Ashley Wiens, Adrián Barahona-Ríos +4
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 developme…
How Far Can VLMs Go for Visual Bug Detection? Studying 19,738 Keyframes from 41 Hours of Gameplay Videos
Wentao Lu, Alexander Senchenko, Alan Sayle +2
Video-based quality assurance (QA) for long-form gameplay video is labor-intensive and error-prone, yet valuable for assessing game stability and visual correctness over extended p…
VideoGameQA-Bench: Evaluating Vision-Language Models for Video Game Quality Assurance
Mohammad Reza Taesiri, Abhijay Ghildyal, Saman Zadtootaghaj +2
With video games now generating the highest revenues in the entertainment industry, optimizing game development workflows has become essential for the sector's sustained growth. Re…
VideoGameBunny: Towards vision assistants for video games
Mohammad Reza Taesiri, Cor-Paul Bezemer
Large multimodal models (LMMs) hold substantial promise across various domains, from personal assistance in daily tasks to sophisticated applications like medical diagnostics. Howe…
GlitchBench: Can large multimodal models detect video game glitches?
Mohammad Reza Taesiri, Tianjun Feng, Anh Nguyen +1
Large multimodal models (LMMs) have evolved from large language models (LLMs) to integrate multiple input modalities, such as visual inputs. This integration augments the capacity…