RESP uses reference-guided sequential prompting with VLMs to improve frame-level and video-level visual glitch detection in games by establishing per-video baselines.
In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
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AdaVFM integrates neural architecture search into vision foundation model backbones and uses a cloud multimodal LLM agent to enable runtime-adaptive lightweight subnet execution, delivering up to 7.9% higher accuracy and 77.9% lower FLOPs than fixed-size baselines on edge devices.
citing papers explorer
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RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games
RESP uses reference-guided sequential prompting with VLMs to improve frame-level and video-level visual glitch detection in games by establishing per-video baselines.
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AdaVFM: Adaptive Vision Foundation Models for Edge Intelligence via LLM-Guided Execution
AdaVFM integrates neural architecture search into vision foundation model backbones and uses a cloud multimodal LLM agent to enable runtime-adaptive lightweight subnet execution, delivering up to 7.9% higher accuracy and 77.9% lower FLOPs than fixed-size baselines on edge devices.