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CLIMB: Confidence-Guided Complementary Evidence for Multimodal Retrieval-Augmented Generation
Multimodal large language models (MLLMs) have shown strong visual reasoning abilities, but knowledge-intensive visual question answering often requires external textual evidence beyond the image and the model's parametric knowledge. Existing multimodal RAG systems commonly rely on Top-$K$ retrieval
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