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• SmoGVLM: A Small, Graph-Enhanced Vision-Language Model

  Large vision-language models (VLMs) have achieved impressive performance across a wide range of multimodal tasks, from visual question answering (VQA) to reasoning over images and text [1, 2]. However, these models often suffer from hallucinations and poor grounding when faced with knowledge-intensive queries.

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