Summary
SciMDR introduces a novel "synthesize-and-reground" framework to create high-quality scientific multimodal document reasoning datasets, addressing the inherent trade-offs in scale, faithfulness, and realism. This two-stage pipeline first generates faithful, isolated QA pairs from focused segments. It then programmatically re-embeds these pairs into full-document tasks, aiming to advance the training of foundation models for scientific understanding.
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