RE-SciVQA: improving scientific VQA with context-relevant retrieval and lightweight MLLM adaptation
Read the original at arxiv.org→arXiv:2611.00242v1 Announce Type: new Abstract: A deep understanding of scientific literature often relies on interpreting figures that contain key information beyond the main text. Leveraging Large Language Models...
Original headline: "RE-SciVQA: Improving Scientific VQA With Context-Relevant Retrieval and Lightweight MLLM Adaptation"
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- Nov 3, 05:00 UTC arXiv cs.AI lead source RE-SciVQA: Improving Scientific VQA With Context-Relevant Retrieval and Lightweight MLLM Adaptation