AI RESEARCH
Aligned Vector Quantization for Edge-Cloud Collabrative Vision-Language Models
arXiv CS.AI
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ArXi:2411.05961v2 Announce Type: replace-cross Vision Language Models (VLMs) are central to Visual Question Answering (VQA) systems and are typically deployed in the cloud due to their high computational demands. However, this cloud-only approach underutilizes edge computational resources and requires significant bandwidth for transmitting raw images. In this paper, we