AI RESEARCH
S1-MMAlign: A Large-Scale, Multi-Disciplinary Dataset for Scientific Figure-Text Understanding
arXiv CS.CV
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ArXi:2601.00264v2 Announce Type: replace Multimodal learning has revolutionized general domain tasks, yet its application in scientific discovery is hindered by the profound semantic gap between complex scientific imagery and sparse textual descriptions. We present S1-MMAlign, a large-scale, multi-disciplinary multimodal dataset comprising over 15.5M high-quality image-text pairs derived from 2.5M open-access scientific papers.