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RE-SciVQA: Improving Scientific VQA With Context-Relevant Retrieval and Lightweight MLLM Adaptation

This story is from 2026-11-04. It is preserved in the archive; the latest stories are on the live feed.

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 (LLMs) to extract insights from these figures can significantly accelerate knowledge…

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  1. 2026-11-04 05:00 · arXiv cs.AI
    RE-SciVQA: Improving Scientific VQA With Context-Relevant Retrieval and Lightweight MLLM Adaptation

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