VLMs are potent tools for grasping visual and textual data, promising advancements in tasks like image captioning and visual question answering. Limited data availability hampers their performance. Recent strides show that pre-training VLMs on larger image-text datasets improves downstream tasks. Yet, creating such datasets faces challenges: scarcity of paired data, high curation costs, low diversity,…