Papers with text-based QA pairs

1 papers
VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search (2025.emnlp-main)

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Challenge: Existing vision-language models struggle with reasoning-focused tasks due to the lack of high-quality training data.
Approach: They propose a new approach that leverages search engines to create a multimodal multimodal dataset . they use a set of 30,000 seed images to extract HTML data from 700K unique URLs .
Outcome: The proposed model achieves the best known performance on MMMU-Pro (40.7), MathVerse (42.6), and DynaMath (55.7).

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